Coursera – Deep Learning Specialization 2021-4 - 磁力狗

BT种子名称

请保存以下最新地址

BT种子基本信息

种子哈希：b7986a473cc7515abfa41d9bfc909ab2076ccb66
文档大小：3.7 GB
文档个数：414个文档
下载次数：771次
下载速度：极快
收录时间：2024-03-12
最近下载：2024-12-31
DMCA/屏蔽：DMCA/屏蔽

下载磁力链接

magnet:?xt=urn:btih:B7986A473CC7515ABFA41D9BFC909AB2076CCB66
复制磁力链接到PikPak、utorrent、Bitcomet、迅雷、115、百度网盘等下载工具进行下载。

下载BT种子

磁力链接种子下载迅雷下载二维码 YouTube成人版 91视频 91短视频 51品茶逼哩逼哩萝莉岛欲漫涩草榴社区含羞草抖阴破解版 TikTok成人版成人快手乱伦社区 91AV 暗网禁地

Coursera – Deep Learning Specialization 2021-4的二维码

文档列表

Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 06 - Geoffrey Hinton Interview.mp4 201.1 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 12 - Yann LeCun Interview.mp4 175.0 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 15 - Yoshua Bengio Interview.mp4 119.7 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 24 - Ruslan Salakhutdinov Interview.mp4 108.6 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 13 - Andrej Karpathy Interview.mp4 88.1 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 25 - Pieter Abbeel Interview.mp4 83.9 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 26 - Yuanqing Lin Interview.mp4 67.4 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 37 - Ian Goodfellow Interview.mp4 57.2 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 21 - Multi-task Learning.mp4 30.4 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 28 - Bleu Score (Optional).mp4 29.6 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 18 - Bias and Variance with Mismatched Data Distributions.mp4 29.4 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 09 - Gated Recurrent Unit (GRU).mp4 28.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 14 - Classic Networks.mp4 28.0 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 15 - Cleaning Up Incorrectly Labeled Data.mp4 27.9 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 35 - Backpropagation Intuition (Optional).mp4 27.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 31 - Bounding Box Predictions.mp4 27.1 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 20 - MobileNet.mp4 26.7 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 44 - Triplet Loss.mp4 26.2 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 37 - TensorFlow.mp4 26.2 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 07 - One Layer of a Convolutional Network.mp4 24.9 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 34 - Self-Attention.mp4 24.7 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 03 - Recurrent Neural Network Model.mp4 24.5 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 32 - Why does Batch Norm work.mp4 24.0 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 20 - Transfer Learning.mp4 23.3 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 14 - Derivatives with a Computation Graph.mp4 22.7 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 36 - Transformer Network.mp4 22.2 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 31 - Fitting Batch Norm into a Neural Network.mp4 21.7 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 02 - Orthogonalization.mp4 21.2 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 07 - When to Change Dev Test Sets and Metrics.mp4 21.0 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 31 - Activation Functions.mp4 20.9 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 43 - Forward and Backward Propagation.mp4 20.8 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 10 - CNN Example.mp4 20.7 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 27 - Object Localization.mp4 20.3 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 16 - Mini-batch Gradient Descent.mp4 20.2 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 50 - Style Cost Function.mp4 20.2 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 22 - What is End-to-end Deep Learning.mp4 20.0 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 14 - Carrying Out Error Analysis.mp4 19.9 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 17 - Training and Testing on Different Distributions.mp4 19.8 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 10 - Understanding Human-level Performance.mp4 19.8 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 10 - Long Short Term Memory (LSTM).mp4 19.7 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 04 - Why is Deep Learning taking off.mp4 19.6 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 34 - Anchor Boxes.mp4 19.5 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 26 - State of Computer Vision.mp4 19.4 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 18 - Word2Vec.mp4 19.3 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 30 - Attention Model.mp4 19.2 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 19 - Addressing Data Mismatch.mp4 18.8 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 19 - Negative Sampling.mp4 18.8 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 25 - Beam Search.mp4 18.8 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 17 - Understanding Mini-batch Gradient Descent.mp4 18.6 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 30 - Convolutional Implementation of Sliding Windows.mp4 18.5 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 06 - Language Model and Sequence Generation.mp4 18.5 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 41 - Why Deep Representations.mp4 18.4 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 23 - Whether to use End-to-end Deep Learning.mp4 18.4 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 34 - Softmax Regression.mp4 18.4 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 15 - Properties of Word Embeddings.mp4 18.2 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 40 - Getting your Matrix Dimensions Right.mp4 18.2 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 10 - Gradient Descent.mp4 17.9 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 01 - Train Dev Test sets.mp4 17.6 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 12 - More Derivative Examples.mp4 17.6 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 22 - Debiasing Word Embeddings.mp4 17.5 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 25 - Data Augmentation.mp4 17.3 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 28 - Computing a Neural Network's Output.mp4 17.1 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 21 - Broadcasting in Python.mp4 17.0 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 17 - Learning Word Embeddings.mp4 16.8 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 34 - Gradient Descent for Neural Networks.mp4 16.8 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 02 - Edge Detection Example.mp4 16.7 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 11 - Why Convolutions.mp4 16.6 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 28 - Using an Appropriate Scale to pick Hyperparameters.mp4 16.6 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 18 - Inception Network Motivation.mp4 16.5 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 30 - Normalizing Activations in a Network.mp4 16.4 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 26 - Refinements to Beam Search.mp4 16.4 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 19 - Understanding Exponentially Weighted Averages.mp4 16.4 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 20 - GloVe Word Vectors.mp4 16.3 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 20 - Vectorizing Logistic Regression's Gradient Output.mp4 16.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 24 - Transfer Learning.mp4 16.2 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 07 - Binary Classification.mp4 16.0 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 13 - Word Representation.mp4 16.0 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 35 - Multi-Head Attention.mp4 15.9 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 37 - Semantic Segmentation with U-Net.mp4 15.8 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 21 - Gradient Descent with Momentum.mp4 15.8 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 27 - Error Analysis in Beam Search.mp4 15.7 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 05 - Different Types of RNNs.mp4 15.6 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 16 - Why ResNets Work.mp4 15.6 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 19 - Inception Network.mp4 15.5 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 29 - Attention Model Intuition.mp4 15.5 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 06 - Convolutions Over Volume.mp4 15.5 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 47 - What are deep ConvNets learning.mp4 15.4 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 21 - MobileNet Architecture.mp4 15.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 41 - What is Face Recognition.mp4 15.0 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 35 - Training a Softmax Classifier.mp4 15.0 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 11 - Bidirectional RNN.mp4 14.9 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 04 - Regularization.mp4 14.9 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 24 - Picking the Most Likely Sentence.mp4 14.8 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 22 - RMSprop.mp4 14.8 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 51 - 1D and 3D Generalizations.mp4 14.8 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 24 - Learning Rate Decay.mp4 14.8 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 04 - Padding.mp4 14.7 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 29 - Vectorizing Across Multiple Examples.mp4 14.5 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 14 - Using Word Embeddings.mp4 14.4 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 09 - Pooling Layers.mp4 14.4 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 07 - Sampling Novel Sequences.mp4 14.4 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 03 - Single Number Evaluation Metric.mp4 14.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 23 - Using Open-Source Implementation.mp4 14.2 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 11 - Derivatives.mp4 14.1 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 02 - Bias Variance.mp4 14.0 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 31 - Speech Recognition.mp4 14.0 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 09 - Logistic Regression Cost Function.mp4 13.8 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 02 - Notation.mp4 13.7 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 23 - Adam Optimization Algorithm.mp4 13.7 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 06 - Dropout Regularization.mp4 13.7 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 39 - Forward Propagation in a Deep Network.mp4 13.7 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 38 - Transpose Convolutions.mp4 13.6 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 03 - Supervised Learning with Neural Networks.mp4 13.5 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 05 - Strided Convolutions.mp4 13.5 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 42 - Building Blocks of Deep Neural Networks.mp4 13.4 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 40 - U-Net Architecture.mp4 13.3 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 17 - Vectorization.mp4 13.2 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 04 - Satisficing and Optimizing Metric.mp4 13.1 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 33 - Non-max Suppression.mp4 13.0 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 22 - A Note on Python Numpy Vectors.mp4 13.0 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 08 - Simple Convolutional Network Example.mp4 13.0 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 16 - Build your First System Quickly, then Iterate.mp4 12.8 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 16 - Gradient Descent on m Examples.mp4 12.8 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 03 - More Edge Detection.mp4 12.8 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 36 - Region Proposals (Optional).mp4 12.7 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 30 - Explanation for Vectorized Implementation.mp4 12.6 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 36 - Random Initialization.mp4 12.5 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 08 - Vanishing Gradients with RNNs.mp4 12.5 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 27 - Tuning Process.mp4 12.4 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 08 - Other Regularization Methods.mp4 12.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 28 - Landmark Detection.mp4 12.2 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 29 - Hyperparameters Tuning in Practice Pandas vs. Caviar.mp4 12.1 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 35 - YOLO Algorithm.mp4 12.1 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 19 - Vectorizing Logistic Regression.mp4 12.0 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 33 - Derivatives of Activation Functions.mp4 11.9 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 06 - Size of the Dev and Test Sets.mp4 11.8 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 09 - Avoidable Bias.mp4 11.8 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 15 - Logistic Regression Gradient Descent.mp4 11.7 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 15 - ResNets.mp4 11.6 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 05 - Train Dev Test Distributions.mp4 11.5 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 08 - Why Human-level Performance.mp4 11.5 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 21 - Sentiment Classification.mp4 11.4 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 01 - Computer Vision.mp4 11.4 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 07 - Understanding Dropout.mp4 11.3 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 10 - Vanishing Exploding Gradients.mp4 11.2 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 04 - Backpropagation Through Time.mp4 11.2 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 12 - Numerical Approximation of Gradients.mp4 11.1 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 24 - Explanation of Logistic Regression Cost Function (Optional).mp4 11.0 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 05 - Why Regularization Reduces Overfitting.mp4 10.9 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 11 - Surpassing Human-level Performance.mp4 10.9 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 38 - Deep L-layer Neural Network.mp4 10.8 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 18 - More Vectorization Examples.mp4 10.8 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 33 - Transformer Network Intuition.mp4 10.8 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 03 - Basic Recipe for Machine Learning.mp4 10.7 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 44 - Parameters vs Hyperparameters.mp4 10.7 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 01 - Welcome.mp4 10.7 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 23 - Basic Models.mp4 10.7 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 11 - Weight Initialization for Deep Networks.mp4 10.6 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 36 - Deep Learning Frameworks.mp4 10.5 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 02 - What is a Neural Network.mp4 10.5 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 33 - Batch Norm at Test Time.mp4 10.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 17 - Networks in Networks and 1x1 Convolutions.mp4 10.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 45 - Face Verification and Binary Classification.mp4 10.2 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 18 - Exponentially Weighted Averages.mp4 10.1 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 13 - Gradient Checking.mp4 10.1 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 29 - Object Detection.mp4 9.8 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 32 - Why do you need Non-Linear Activation Functions.mp4 9.7 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 23 - Quick tour of Jupyter iPython Notebooks.mp4 9.7 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 12 - Improving your Model Performance.mp4 9.6 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 14 - Gradient Checking Implementation Notes.mp4 9.6 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 20 - Bias Correction in Exponentially Weighted Averages.mp4 9.5 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 22 - EfficientNet.mp4 9.5 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 25 - The Problem of Local Optima.mp4 9.4 MB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 09 - Normalizing Inputs.mp4 9.3 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 16 - Embedding Matrix.mp4 9.1 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 12 - Deep RNNs.mp4 9.0 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 08 - Logistic Regression.mp4 8.9 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 27 - Neural Network Representation.mp4 8.7 MB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 01 - Why ML Strategy.mp4 8.6 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 13 - Why look at case studies.mp4 8.3 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 43 - Siamese Network.mp4 7.9 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 42 - One Shot Learning.mp4 7.8 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 26 - Neural Networks Overview.mp4 7.6 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 32 - Intersection Over Union.mp4 7.6 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 32 - Trigger Word Detection.mp4 7.4 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 48 - Cost Function.mp4 7.0 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 39 - U-Net Architecture Intuition.mp4 6.3 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 45 - What does this have to do with the brain.mp4 6.3 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 13 - Computation Graph.mp4 5.9 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 49 - Content Cost Function.mp4 5.9 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 01 - Why Sequence Models.mp4 5.5 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 37 - Conclusion and Thank You!.mp4 5.5 MB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 05 - About this Course.mp4 4.9 MB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 46 - What is Neural Style Transfer.mp4 4.8 MB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 01 - Why Sequence Models.mp4.jpg 249.9 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 01 - Why Sequence Models.mp4.vtx 249.9 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 03 - Recurrent Neural Network Model.mp4.jpg 223.4 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 03 - Recurrent Neural Network Model.mp4.vtx 223.4 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 02 - Notation.mp4.jpg 194.0 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 02 - Notation.mp4.vtx 194.0 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 06 - Geoffrey Hinton Interview.hi.srt 114.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 06 - Geoffrey Hinton Interview.en.srt 58.9 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 12 - Yann LeCun Interview.en.srt 41.9 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 15 - Yoshua Bengio Interview.en.srt 35.0 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 04 - Why is Deep Learning taking off.hi.srt 29.9 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 41 - Why Deep Representations.hi.srt 29.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 21 - Broadcasting in Python.hi.srt 27.8 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 13 - Andrej Karpathy Interview.en.srt 27.6 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 25 - Pieter Abbeel Interview.en.srt 27.5 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 31 - Activation Functions.hi.srt 27.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 14 - Classic Networks.en.srt 25.1 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 24 - Ruslan Salakhutdinov Interview.en.srt 24.6 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 18 - Bias and Variance with Mismatched Data Distributions.en.srt 23.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 03 - Supervised Learning with Neural Networks.hi.srt 23.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 37 - Ian Goodfellow Interview.en.srt 23.6 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 09 - Gated Recurrent Unit (GRU).en.srt 23.2 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 20 - MobileNet.en.srt 22.8 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 44 - Triplet Loss.en.srt 22.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 35 - Backpropagation Intuition (Optional).en.srt 21.1 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 03 - Recurrent Neural Network Model.en.srt 20.5 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 31 - Bounding Box Predictions.en.srt 20.5 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 37 - TensorFlow.en.srt 20.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 02 - What is a Neural Network.hi.srt 19.7 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 15 - Cleaning Up Incorrectly Labeled Data.en.srt 19.6 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 22 - What is End-to-end Deep Learning.en.srt 19.4 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 28 - Bleu Score (Optional).en.srt 19.3 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 21 - Multi-task Learning.en.srt 19.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 29 - Vectorizing Across Multiple Examples.hi.srt 19.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 07 - One Layer of a Convolutional Network.en.srt 19.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 04 - Why is Deep Learning taking off.en.srt 18.3 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 26 - State of Computer Vision.en.srt 18.3 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 17 - Vectorization.hi.srt 18.0 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 26 - Yuanqing Lin Interview.en.srt 17.8 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 01 - Train Dev Test sets.en.srt 17.6 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 01 - Welcome.hi.srt 17.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 33 - Derivatives of Activation Functions.hi.srt 17.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 50 - Style Cost Function.en.srt 17.1 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 20 - Transfer Learning.en.srt 17.0 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 32 - Why does Batch Norm work.en.srt 16.8 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 14 - Derivatives with a Computation Graph.en.srt 16.7 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 18 - Word2Vec.en.srt 16.5 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 02 - What is a Neural Network.el.srt 16.3 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 34 - Self-Attention.en.srt 16.2 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 25 - Beam Search.en.srt 16.2 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 31 - Fitting Batch Norm into a Neural Network.en.srt 16.0 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 19 - Negative Sampling.en.srt 15.8 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 06 - Language Model and Sequence Generation.en.srt 15.8 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 10 - Gradient Descent.en.srt 15.7 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 10 - CNN Example.en.srt 15.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 28 - Computing a Neural Network's Output.en.srt 15.6 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 14 - Carrying Out Error Analysis.en.srt 15.5 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 07 - When to Change Dev Test Sets and Metrics.en.srt 15.5 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 10 - Understanding Human-level Performance.en.srt 15.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 27 - Neural Network Representation.hi.srt 15.3 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 02 - Orthogonalization.en.srt 15.3 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 17 - Learning Word Embeddings.en.srt 15.1 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 34 - Softmax Regression.en.srt 15.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 41 - Why Deep Representations.en.srt 15.0 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 30 - Attention Model.en.srt 15.0 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 13 - Word Representation.en.srt 15.0 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 22 - Debiasing Word Embeddings.en.srt 15.0 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 19 - Addressing Data Mismatch.en.srt 14.9 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 27 - Object Localization.en.srt 14.8 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 02 - Edge Detection Example.en.srt 14.8 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 20 - GloVe Word Vectors.en.srt 14.7 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 09 - Pooling Layers.en.srt 14.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 31 - Activation Functions.en.srt 14.6 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 23 - Whether to use End-to-end Deep Learning.en.srt 14.6 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 17 - Training and Testing on Different Distributions.en.srt 14.6 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 30 - Convolutional Implementation of Sliding Windows.en.srt 14.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 21 - Broadcasting in Python.en.srt 14.3 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 06 - Dropout Regularization.en.srt 14.2 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 17 - Understanding Mini-batch Gradient Descent.en.srt 14.2 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 02 - Bias Variance.en.srt 14.0 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 15 - Properties of Word Embeddings.en.srt 14.0 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 26 - Refinements to Beam Search.en.srt 14.0 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 19 - Understanding Exponentially Weighted Averages.en.srt 14.0 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 06 - Convolutions Over Volume.en.srt 14.0 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 35 - Training a Softmax Classifier.en.srt 13.8 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 43 - Forward and Backward Propagation.en.srt 13.8 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 11 - Why Convolutions.en.srt 13.5 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 10 - Long Short Term Memory (LSTM).en.srt 13.5 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 16 - Mini-batch Gradient Descent.en.srt 13.3 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 29 - Attention Model Intuition.en.srt 13.3 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 44 - Parameters vs Hyperparameters.en.srt 13.3 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 18 - Inception Network Motivation.en.srt 13.3 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 05 - Different Types of RNNs.en.srt 13.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 12 - More Derivative Examples.en.srt 13.2 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 34 - Anchor Boxes.en.srt 13.1 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 14 - Using Word Embeddings.en.srt 13.1 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 27 - Error Analysis in Beam Search.en.srt 13.0 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 08 - Other Regularization Methods.en.srt 12.9 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 32 - Why do you need Non-Linear Activation Functions.hi.srt 12.8 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 04 - Regularization.en.srt 12.7 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 04 - Padding.en.srt 12.7 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 21 - Gradient Descent with Momentum.en.srt 12.6 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 24 - Picking the Most Likely Sentence.en.srt 12.6 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 21 - MobileNet Architecture.en.srt 12.5 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 25 - Data Augmentation.en.srt 12.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 34 - Gradient Descent for Neural Networks.en.srt 12.3 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 03 - Supervised Learning with Neural Networks.en.srt 12.2 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 33 - Non-max Suppression.en.srt 12.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 26 - Neural Networks Overview.hi.srt 12.1 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 31 - Speech Recognition.en.srt 11.8 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 35 - Multi-Head Attention.en.srt 11.8 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 02 - Notation.en.srt 11.7 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 21 - Sentiment Classification.en.srt 11.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 40 - Getting your Matrix Dimensions Right.en.srt 11.7 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 16 - Why ResNets Work.en.srt 11.7 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 07 - Sampling Novel Sequences.en.srt 11.6 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 51 - 1D and 3D Generalizations.en.srt 11.6 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 24 - Transfer Learning.en.srt 11.6 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 37 - Semantic Segmentation with U-Net.en.srt 11.5 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 30 - Normalizing Activations in a Network.en.srt 11.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 09 - Logistic Regression Cost Function.en.srt 11.3 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 05 - Train Dev Test Distributions.en.srt 11.3 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 28 - Using an Appropriate Scale to pick Hyperparameters.en.srt 11.3 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 05 - Strided Convolutions.en.srt 11.2 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 47 - What are deep ConvNets learning.en.srt 11.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 16 - Gradient Descent on m Examples.en.srt 11.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 23 - Quick tour of Jupyter iPython Notebooks.hi.srt 11.2 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 07 - Understanding Dropout.en.srt 11.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 11 - Derivatives.en.srt 11.1 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 27 - Tuning Process.en.srt 11.1 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 29 - Hyperparameters Tuning in Practice Pandas vs. Caviar.en.srt 11.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 19 - Inception Network.en.srt 11.0 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 20 - Vectorizing Logistic Regression's Gradient Output.en.srt 11.0 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 38 - Transpose Convolutions.en.srt 10.9 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 07 - Binary Classification.en.srt 10.8 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 03 - More Edge Detection.en.srt 10.8 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 03 - Basic Recipe for Machine Learning.en.srt 10.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 36 - Random Initialization.el.srt 10.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 36 - Random Initialization.en.srt 10.6 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 33 - Derivatives of Activation Functions.en.srt 10.6 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 11 - Bidirectional RNN.en.srt 10.6 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 29 - Vectorizing Across Multiple Examples.en.srt 10.3 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 35 - YOLO Algorithm.en.srt 10.2 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 22 - RMSprop.en.srt 10.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 02 - What is a Neural Network.en.srt 10.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 40 - U-Net Architecture.en.srt 10.1 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 05 - Why Regularization Reduces Overfitting.en.srt 10.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 08 - Simple Convolutional Network Example.en.srt 10.0 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 03 - Single Number Evaluation Metric.en.srt 9.9 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 17 - Vectorization.en.srt 9.8 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 19 - Vectorizing Logistic Regression.en.srt 9.8 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 15 - ResNets.en.srt 9.7 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 08 - Vanishing Gradients with RNNs.en.srt 9.7 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 36 - Region Proposals (Optional).en.srt 9.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 45 - What does this have to do with the brain.hi.srt 9.6 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 42 - Building Blocks of Deep Neural Networks.en.srt 9.6 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 09 - Avoidable Bias.en.srt 9.5 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 13 - Gradient Checking.en.srt 9.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 22 - A Note on Python Numpy Vectors.en.srt 9.3 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 24 - Learning Rate Decay.en.srt 9.2 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 12 - Numerical Approximation of Gradients.en.srt 9.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 15 - Logistic Regression Gradient Descent.en.srt 9.2 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 39 - Forward Propagation in a Deep Network.en.srt 9.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 01 - Computer Vision.en.srt 9.1 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 11 - Surpassing Human-level Performance.en.srt 9.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 05 - About this Course.kn.srt 9.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 01 - Welcome.en.srt 9.1 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 18 - Exponentially Weighted Averages.en.srt 9.0 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 30 - Explanation for Vectorized Implementation.en.srt 8.9 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 23 - Adam Optimization Algorithm.en.srt 8.8 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 24 - Explanation of Logistic Regression Cost Function (Optional).en.srt 8.7 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 17 - Networks in Networks and 1x1 Convolutions.en.srt 8.7 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 16 - Build your First System Quickly, then Iterate.en.srt 8.6 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 05 - About this Course.hi.srt 8.5 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 25 - The Problem of Local Optima.en.srt 8.5 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 23 - Basic Models.en.srt 8.5 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 10 - Vanishing Exploding Gradients.en.srt 8.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 27 - Neural Network Representation.en.srt 8.3 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 04 - Backpropagation Through Time.en.srt 8.3 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 08 - Why Human-level Performance.en.srt 8.2 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 11 - Weight Initialization for Deep Networks.en.srt 8.2 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 04 - Satisficing and Optimizing Metric.en.srt 8.2 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 06 - Size of the Dev and Test Sets.en.srt 8.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 45 - Face Verification and Binary Classification.en.srt 8.0 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 29 - Object Detection.en.srt 8.0 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 14 - Gradient Checking Implementation Notes.en.srt 8.0 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 33 - Batch Norm at Test Time.en.srt 8.0 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 28 - Landmark Detection.en.srt 7.8 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 08 - Logistic Regression.en.srt 7.7 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 09 - Normalizing Inputs.en.srt 7.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 38 - Deep L-layer Neural Network.en.srt 7.6 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 18 - More Vectorization Examples.en.srt 7.6 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 16 - Embedding Matrix.en.srt 7.4 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 23 - Using Open-Source Implementation.en.srt 6.9 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 12 - Deep RNNs.en.srt 6.9 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 32 - Why do you need Non-Linear Activation Functions.en.srt 6.7 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 41 - What is Face Recognition.en.srt 6.7 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 42 - One Shot Learning.en.srt 6.7 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 36 - Deep Learning Frameworks.en.srt 6.6 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 33 - Transformer Network Intuition.en.srt 6.5 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 12 - Improving your Model Performance.en.srt 6.4 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 43 - Siamese Network.en.srt 6.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 26 - Neural Networks Overview.en.srt 6.1 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 32 - Trigger Word Detection.en.srt 6.1 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 23 - Quick tour of Jupyter iPython Notebooks.en.srt 5.9 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 22 - EfficientNet.en.srt 5.8 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 32 - Intersection Over Union.en.srt 5.7 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 13 - Computation Graph.en.srt 5.6 kB
Coursera – Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization 2021-4/deep-neural-network - 20 - Bias Correction in Exponentially Weighted Averages.en.srt 5.3 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 48 - Cost Function.en.srt 5.3 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 49 - Content Cost Function.en.srt 5.0 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 45 - What does this have to do with the brain.en.srt 4.9 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 13 - Why look at case studies.en.srt 4.9 kB
Coursera – Structuring Machine Learning Projects 2021-4/machine-learning-projects - 01 - Why ML Strategy.en.srt 4.6 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 01 - Why Sequence Models.en.srt 4.6 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 05 - About this Course.en.srt 4.5 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 39 - U-Net Architecture Intuition.en.srt 4.4 kB
Coursera – Neural Networks and Deep Learning 2021-4/neural-networks-deep-learning - 05 - About this Course.hr.srt 4.3 kB
Coursera - Sequence Models 2021-4-23/nlp-sequence-models - 37 - Conclusion and Thank You!.en.srt 4.1 kB
Coursera – Convolutional Neural Networks 2021-4/convolutional-neural-networks - 46 - What is Neural Style Transfer.en.srt 2.9 kB

==查看完整文档列表==

下一个：【高清影视之家发布 www.HDBTHD.com】贴身情人[简繁英字幕].Two.Weeks.Notice.2002.BluRay.1080p.DTS-HDMA5.1.x265.10bit-DreamHD 8.5 GB