- 【影视】 [GigaCourse.Com] Udemy - TensorFlow Developer Certificate in 2022 Zero to Mastery
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[GigaCourse.Com] Udemy - TensorFlow Developer Certificate in 2022 Zero to Mastery 29.1 GB
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- 【影视】 Tensorflow 2.0 Um Guia Completo sobre o novo TensorFlow
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16. Anexo III - Redes Neurais Recorrentes - teoria/4. Intuição prática.mp4 166.4 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/3. Long short term memory - LSTM.mp4 104.1 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/1. O que são Redes Neurais Recorrentes.mp4 103.1 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/2. A Equação de Bellman.mp4 95.1 MB
14. Anexo I - Redes Neurais Artificiais - teoria/9. Funções de ativação II.mp4 81.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/2. Introdução a redes neurais convolucionais II.mp4 80.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/1. Introdução a redes neurais convolucionais I.mp4 75.9 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/12. Treinamento II.mp4 75.6 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/11. Replay de Experiência.mp4 75.2 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/12. Políticas de Seleções de Ações.mp4 74.6 MB
2. Básico do TensorFlow/1. Do TensorFlow 1.x para o TensorFlow 2.0 - Constantes, variáveis e tensores.mp4 72.9 MB
1. Introdução/1. Bem-vindo(a) ao curso!.mp4 72.3 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/2. Problema do gradiente desaparecendo (vanish gradient problem).mp4 71.0 MB
10. API com Flask e TensorFlow 2.0/1. Configuração do Projeto.mp4 70.3 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/4. Markov Decision Process - MDP.mp4 70.3 MB
5. Redes Neurais Recorrentes/1. Configuração do Projeto e Pré-processamento.mp4 66.1 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/6. Etapa 3 - flattening.mp4 65.8 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/7. Etapa 4 - rede neural densa.mp4 65.3 MB
9. Pré-processamento de Dados com TFT (TensorFlow Transform)/5. Pipeline de Pré-processamento.mp4 63.7 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/6. IA Trader 5.mp4 63.4 MB
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14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.mp4 151.3 MB
1. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.mp4 110.9 MB
13. Business case/4. Preprocessing the data.mp4 88.4 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 69.5 MB
13. Business case/9. Setting an early stopping mechanism.mp4 52.2 MB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4 52.2 MB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4 51.8 MB
12. The MNIST example/6. Preprocess the data - shuffle and batch the data.mp4 43.6 MB
12. The MNIST example/10. Learning.mp4 42.9 MB
2. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 MB
3. Setting up the working environment/9. Installing TensorFlow 2.mp4 40.6 MB
2. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.mp4 40.1 MB
14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.mp4 39.9 MB
5. TensorFlow - An introduction/5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4 36.4 MB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4 35.5 MB
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.mp4 35.2 MB
5. TensorFlow - An introduction/1. TensorFlow outline.mp4 35.2 MB
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4 34.2 MB
3. Setting up the working environment/2. Why Python and why Jupyter.mp4 33.6 MB
13. Business case/8. Learning and interpreting the result.mp4 32.7 MB
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- 【影视】 Deep Learning Image Classification with Tensorflow in 2023
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[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/18 - Deploying the Image classification model/84 - Building API with Fastapi.mp4 707.7 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/8 - Data Augmentation/44 - Albumentations with TensorFlow 2 and PyTorch for Data augmentation.mp4 647.5 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/11 - MLOps with Weights and Biases/52 - Experiment Tracking.mp4 492.5 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/8 - Data Augmentation/41 - Data augmentation with TensorFlow using tfimage and Keras Layers.mp4 444.6 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/17 - Transformers in Vision/72 - Understanding VITs.mp4 442.5 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/2 - Tensors and variables/4 - Initialization and Casting.mp4 426.3 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/17 - Transformers in Vision/73 - Building VITs from scratch.mp4 418.0 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/12 - Human Emotions Detection/57 - Modeling and Training.mp4 390.0 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/2 - Tensors and variables/7 - Linear Algebra Operations.mp4 389.5 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/13 - Modern Convolutional Neural Networks/62 - resnet.mp4 368.9 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/4 - Building convnets with tensorflow/25 - How and Why Convolutional Neural Networks Work.mp4 365.6 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/8 - Data Augmentation/43 - Cutmix Data augmentation with TensorFlow 2 and intergration in tfdata.mp4 360.9 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/11 - MLOps with Weights and Biases/54 - Dataset Versioning with Weights and Biases and TensorFlow 2.mp4 345.5 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/2 - Tensors and variables/8 - Common Methods.mp4 313.6 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/12 - Human Emotions Detection/59 - Tensorflow records.mp4 307.9 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/10 - Tensorboard integration with TensorFlow 2/48 - Log data.mp4 301.2 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/3 - PREREQUISCITE Building neural networks with Tensorflow/14 - Data Preparation.mp4 289.8 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/18 - Deploying the Image classification model/79 - Understanding quantization.mp4 281.2 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/9 - Advanced Tensorflow/47 - Custom Training Loops in TensorFlow 2.mp4 246.3 MB
[TutsNode.net] - Deep Learning Image Classification with Tensorflow in 2023/15 - Understanding the blackbox/69 - gradcam method.mp4 237.8 MB
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01 - Introduction/001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit.mp4 153.4 MB
02 - TensorFlow 2.0 Basics/001 From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
17 - Annex 3 - Recurrent Neural Networks Theory/005 LSTM Practical Intuition.mp4 112.7 MB
17 - Annex 3 - Recurrent Neural Networks Theory/004 LSTMs.mp4 93.2 MB
16 - Annex 2 - Convolutional Neural Networks Theory/005 Step 2 - Max Pooling.mp4 91.7 MB
17 - Annex 3 - Recurrent Neural Networks Theory/003 Vanishing Gradient.mp4 90.4 MB
16 - Annex 2 - Convolutional Neural Networks Theory/002 What are Convolutional Neural Networks.mp4 74.5 MB
16 - Annex 2 - Convolutional Neural Networks Theory/003 Step 1 - Convolution.mp4 68.8 MB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/005 Dataset preprocessing pipeline.mp4 62.7 MB
16 - Annex 2 - Convolutional Neural Networks Theory/007 Step 4 - Full Connection.mp4 61.4 MB
17 - Annex 3 - Recurrent Neural Networks Theory/002 What are Recurrent Neural Networks.mp4 60.3 MB
04 - Convolutional Neural Networks/002 Building the Convolutional Neural Network.mp4 59.3 MB
07 - Deep Reinforcement Learning Theory/009 Action Selection Policies.mp4 57.0 MB
16 - Annex 2 - Convolutional Neural Networks Theory/009 Softmax & Cross-Entropy.mp4 53.9 MB
07 - Deep Reinforcement Learning Theory/002 The Bellman Equation.mp4 50.6 MB
06 - Transfer Learning and Fine Tuning/001 What is Transfer Learning.mp4 48.7 MB
06 - Transfer Learning and Fine Tuning/002 Project Setup.mp4 46.6 MB
15 - Annex 1 - Artificial Neural Networks Theory/002 The Neuron.mp4 45.8 MB
15 - Annex 1 - Artificial Neural Networks Theory/005 How do Neural Networks Learn.mp4 45.4 MB
07 - Deep Reinforcement Learning Theory/003 Markov Decision Process (MDP).mp4 44.4 MB
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16. Anexo III - Redes Neurais Recorrentes - teoria/4. Intuição prática.mp4 166.4 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/3. Long short term memory - LSTM.mp4 104.1 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/1. O que são Redes Neurais Recorrentes.mp4 103.1 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/2. A Equação de Bellman.mp4 95.1 MB
14. Anexo I - Redes Neurais Artificiais - teoria/9. Funções de ativação II.mp4 81.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/2. Introdução a redes neurais convolucionais II.mp4 80.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/1. Introdução a redes neurais convolucionais I.mp4 75.9 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/12. Treinamento II.mp4 75.6 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/11. Replay de Experiência.mp4 75.2 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/12. Políticas de Seleções de Ações.mp4 74.6 MB
2. Básico do TensorFlow/1. Do TensorFlow 1.x para o TensorFlow 2.0 - Constantes, variáveis e tensores.mp4 72.9 MB
1. Introdução/1. Bem-vindo(a) ao curso!.mp4 72.3 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/2. Problema do gradiente desaparecendo (vanish gradient problem).mp4 71.0 MB
10. API com Flask e TensorFlow 2.0/1. Configuração do Projeto.mp4 70.3 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/4. Markov Decision Process - MDP.mp4 70.3 MB
5. Redes Neurais Recorrentes/1. Configuração do Projeto e Pré-processamento.mp4 66.1 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/6. Etapa 3 - flattening.mp4 65.8 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/7. Etapa 4 - rede neural densa.mp4 65.3 MB
9. Pré-processamento de Dados com TFT (TensorFlow Transform)/5. Pipeline de Pré-processamento.mp4 63.7 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/6. IA Trader 5.mp4 63.4 MB
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~Get Your Files Here !/2. Creating Deep Neural Networks/2.3 Using Real-World Data With a Neural Network.mp4 53.8 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.4 Creating a Convolutional Network for Image Classification.mp4 47.7 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.5 Training and Using a Convolutional Network.mp4 36.2 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.2 Training and Using Your Neural Network.mp4 34.3 MB
~Get Your Files Here !/1. Introduction/1.3 Setting Up TensorFlow.mp4 33.0 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.1 Creating Your First Neural Network.mp4 26.6 MB
~Get Your Files Here !/1. Introduction/1.2 Why Use TensorFlow.mp4 18.2 MB
~Get Your Files Here !/3. Conclusion/3.1 Conclusion.mp4 10.3 MB
~Get Your Files Here !/1. Introduction/1.1 Introduction.mp4 10.0 MB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.4 Creating a Convolutional Network for Image Classification.vtt 12.5 kB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.3 Using Real-World Data With a Neural Network.vtt 11.3 kB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.1 Creating Your First Neural Network.vtt 10.1 kB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.2 Training and Using Your Neural Network.vtt 7.6 kB
~Get Your Files Here !/2. Creating Deep Neural Networks/2.5 Training and Using a Convolutional Network.vtt 4.7 kB
~Get Your Files Here !/1. Introduction/1.2 Why Use TensorFlow.vtt 2.9 kB
~Get Your Files Here !/1. Introduction/1.3 Setting Up TensorFlow.vtt 2.8 kB
~Get Your Files Here !/3. Conclusion/3.1 Conclusion.vtt 1.3 kB
~Get Your Files Here !/1. Introduction/1.1 Introduction.vtt 1.3 kB
~Get Your Files Here !/Bonus Resources.txt 357 Bytes
Get Bonus Downloads Here.url 183 Bytes
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09 Project Facial Expression Recognition/028 Class-Based ANN in Theano.mp4 46.1 MB
10 Appendix/031 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 46.0 MB
09 Project Facial Expression Recognition/029 Class-Based ANN in TensorFlow.mp4 39.2 MB
07 GPU Speedup Homework and Other Misc Topics/018 Setting up a GPU Instance on Amazon Web Services.mp4 26.9 MB
10 Appendix/032 How to Code by Yourself part 1.mp4 25.7 MB
06 TensorFlow/017 Building a neural network in TensorFlow.mp4 25.0 MB
08 Modern Regularization Techniques/023 Dropout Regularization.mp4 23.8 MB
05 Theano/015 Building a neural network in Theano.mp4 22.8 MB
09 Project Facial Expression Recognition/025 Facial Expression Recognition Problem Description.mp4 22.5 MB
05 Theano/014 Theano Basics Variables Functions Expressions Optimization.mp4 20.3 MB
06 TensorFlow/016 TensorFlow Basics Variables Functions Expressions Optimization.mp4 17.9 MB
10 Appendix/033 How to Code by Yourself part 2.mp4 15.5 MB
03 Momentum and adaptive learning rates/008 Code for training a neural network using momentum.mp4 15.3 MB
02 Gradient Descent Full vs Batch vs Stochastic/006 Full vs Batch vs Stochastic Gradient Descent in code.mp4 14.7 MB
04 Choosing Hyperparameters/012 Grid Search in Code.mp4 14.4 MB
09 Project Facial Expression Recognition/027 Utilities walkthrough.mp4 14.1 MB
01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/004 Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 11.7 MB
03 Momentum and adaptive learning rates/010 Constant learning rate vs. RMSProp in Code.mp4 11.5 MB
09 Project Facial Expression Recognition/026 The class imbalance problem.mp4 10.6 MB
07 GPU Speedup Homework and Other Misc Topics/022 Theano vs. TensorFlow.mp4 9.6 MB
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21 Gerac227o automatica de caracteres/102 Construc227o da GAN - MNIST IV.mp4 152.5 MB
12 Classificac227o de digitos escritos a m227o/073 Redes convolucionais com estimators V.mp4 148.6 MB
09 Redes neurais para classificac227o e regress227o com TensorFlow/051 Classificac227o multiclasse - base iris II.mp4 144.3 MB
06 Classificac227o/031 Regress227o logistica com estimators I.mp4 144.0 MB
15 Serie temporal - precos da bolsa de valores/081 Base de dados para redes recorrentes II.mp4 142.9 MB
21 Gerac227o automatica de caracteres/101 Construc227o da GAN - MNIST III.mp4 138.2 MB
15 Serie temporal - precos da bolsa de valores/080 Base de dados para redes recorrentes I.mp4 127.0 MB
09 Redes neurais para classificac227o e regress227o com TensorFlow/050 Classificac227o multiclasse - base iris I.mp4 121.6 MB
22 Ap234ndice A - Basico sobre aprendizagem de maquina/107 Introduc227o a avaliac227o de algoritmos.mp4 118.3 MB
15 Serie temporal - precos da bolsa de valores/083 Redes neurais recorrentes II.mp4 117.2 MB
08 Teoria resumida sobre redes neurais artificiais/043 TensorFlow playground.mp4 113.6 MB
21 Gerac227o automatica de caracteres/100 Construc227o da GAN - MNIST II.mp4 113.2 MB
09 Redes neurais para classificac227o e regress227o com TensorFlow/055 Classificac227o de digitos manuscritos III.mp4 112.7 MB
12 Classificac227o de digitos escritos a m227o/072 Redes convolucionais com estimators IV.mp4 112.6 MB
18 Reduc227o de dimensionalidade/094 Stacked autoencoder - MNIST III.mp4 111.7 MB
09 Redes neurais para classificac227o e regress227o com TensorFlow/048 Classificac227o binaria - XOR II.mp4 111.7 MB
05 Regress227o linear/025 Regress227o linear simples com estimators II.mp4 110.6 MB
05 Regress227o linear/027 Regress227o linear multipla com estimators II.mp4 109.3 MB
21 Gerac227o automatica de caracteres/099 Construc227o da GAN - MNIST I.mp4 107.4 MB
22 Ap234ndice A - Basico sobre aprendizagem de maquina/108 Introduc227o a redes neurais artificiais I.mp4 106.7 MB
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14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.mp4 151.3 MB
01. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.mp4 110.9 MB
13. Business case/4. Preprocessing the data.mp4 96.5 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 82.0 MB
13. Business case/9. Setting an early stopping mechanism.mp4 56.0 MB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4 52.2 MB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4 51.8 MB
12. The MNIST example/6. Preprocess the data - shuffle and batch the data.mp4 48.2 MB
12. The MNIST example/10. Learning.mp4 46.6 MB
03. Setting up the working environment/9. Installing TensorFlow 2.mp4 45.0 MB
03. Setting up the working environment/2. Why Python and why Jupyter.mp4 43.0 MB
02. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 MB
05. TensorFlow - An introduction/1. TensorFlow outline.mp4 40.2 MB
02. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.mp4 40.1 MB
05. TensorFlow - An introduction/5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4 40.1 MB
14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.mp4 39.9 MB
13. Business case/3. Balancing the dataset.mp4 36.9 MB
03. Setting up the working environment/4. Installing Anaconda.mp4 36.6 MB
13. Business case/8. Learning and interpreting the result.mp4 36.3 MB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4 35.5 MB
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18. Setting up your Environment/2. Windows-Focused Environment Setup 2018.mp4 203.4 MB
18. Setting up your Environment/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 175.4 MB
18. Setting up your Environment/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 174.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 150.1 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 130.5 MB
20. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 128.6 MB
20. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 122.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 108.2 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 102.5 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 96.7 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 96.5 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 95.4 MB
2. Google Colab/3. Uploading your own data to Google Colab.mp4 93.4 MB
20. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 92.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 91.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 91.5 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 90.7 MB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 90.6 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 90.5 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 88.0 MB
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6 - Transfer Learning with TensorFlow/4 - Implementing Transfer Learning in TensorFlow.mp4 40.0 MB
3 - Introducing TensorFlow/2 - Installing TensorFlow.mp4 32.0 MB
3 - Introducing TensorFlow/5 - TensorFlow Training.mp4 27.0 MB
tensorflow-getting-started.zip 23.9 MB
4 - Creating Neural Networks in TensorFlow/4 - Simple MNIST.mp4 23.4 MB
4 - Creating Neural Networks in TensorFlow/6 - Coding Deep MNIST.mp4 23.3 MB
7 - Extending TensorFlow with Add-ons/3 - Using Keras.mp4 22.1 MB
5 - Debugging and Monitoring/6 - Using TensorBoard - Part 2.mp4 19.4 MB
7 - Extending TensorFlow with Add-ons/4 - DeepMNIST in Keras.mp4 18.5 MB
5 - Debugging and Monitoring/3 - Using Names and Name Scope.mp4 18.1 MB
5 - Debugging and Monitoring/5 - Using TensorBoard - Part 1.mp4 16.4 MB
6 - Transfer Learning with TensorFlow/5 - Retraining Inception.mp4 15.5 MB
6 - Transfer Learning with TensorFlow/6 - Using Our Retrained Model.mp4 14.7 MB
7 - Extending TensorFlow with Add-ons/7 - DeepMNIST in TFLearn.mp4 14.4 MB
7 - Extending TensorFlow with Add-ons/6 - Using TFLearn.mp4 14.2 MB
4 - Creating Neural Networks in TensorFlow/5 - Deep MNIST.mp4 8.4 MB
2 - Introduction/4 - Skills and Course Structure.mp4 8.2 MB
3 - Introducing TensorFlow/8 - Gradient Descent in Action.mp4 7.2 MB
3 - Introducing TensorFlow/7 - Gradient Descent.mp4 6.4 MB
3 - Introducing TensorFlow/3 - Getting Hands-on.mp4 6.3 MB
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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 147.0 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB
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6. Live Projects/3. Cats vs Dogs.mp4 303.6 MB
6. Live Projects/1. Fashion Clothing Recognition.mp4 164.3 MB
5. Section 5/8. Facial Recognition using PCA.mp4 156.4 MB
3. Section 3/4. Backpropagation.mp4 154.3 MB
3. Section 3/6. Digit Classification.mp4 151.4 MB
2. Section 2/3. Linear Regression - Theory.mp4 151.1 MB
2. Section 2/1. Decision Trees - Theory.mp4 145.5 MB
4. Section 4/2. Convolution in CNN (part1).mp4 143.9 MB
4. Section 4/3. Convolution in CNN (part2).mp4 138.1 MB
2. Section 2/6. Logistic Regression - Implementation.mp4 123.0 MB
4. Section 4/4. Layers of CNN.mp4 119.4 MB
1. Section 1/6. Intro to Machine Learning.mp4 117.9 MB
1. Section 1/3. Graphs.mp4 117.7 MB
3. Section 3/3. Complex Decision Boundaries.mp4 117.1 MB
5. Section 5/7. Principal Component Analysis.mp4 115.2 MB
4. Section 4/1. Introduction.mp4 114.4 MB
2. Section 2/5. Logistic Regression - Theory.mp4 112.8 MB
3. Section 3/2. Gates and Forward Propagation.mp4 109.3 MB
2. Section 2/4. Linear Regression - Implementation.mp4 109.1 MB
5. Section 5/2. K-Means Algorithm (Part 2).mp4 108.2 MB
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18. Setting up your Environment/2. Windows-Focused Environment Setup 2018.mp4 203.4 MB
18. Setting up your Environment/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 175.4 MB
18. Setting up your Environment/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 174.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 150.1 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 130.5 MB
19. Appendix FAQ/9. What order should I take your courses in (part 2).mp4 128.6 MB
19. Appendix FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 122.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 108.2 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 102.5 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 96.7 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 96.5 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 95.4 MB
2. Google Colab/3. Uploading your own data to Google Colab.mp4 93.4 MB
19. Appendix FAQ/8. What order should I take your courses in (part 1).mp4 92.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 91.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 91.5 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 90.7 MB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 90.5 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 90.5 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 88.0 MB
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18. Setting up your Environment/2. Windows-Focused Environment Setup 2018.mp4 203.4 MB
18. Setting up your Environment/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 175.4 MB
18. Setting up your Environment/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 174.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 150.1 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 130.5 MB
19. Appendix FAQ/9. What order should I take your courses in (part 2).mp4 128.6 MB
19. Appendix FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 122.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 108.2 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 102.5 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 96.6 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 96.5 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 95.4 MB
2. Google Colab/3. Uploading your own data to Google Colab.mp4 93.4 MB
19. Appendix FAQ/8. What order should I take your courses in (part 1).mp4 92.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 91.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 91.5 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 90.7 MB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 90.5 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 90.5 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 88.0 MB
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