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【影视】 GetFreeCourses.Co-Udemy-TensorFlow Developer Certificate in 2021 Zero to Mastery

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GetFreeCourses.Co-Udemy-TensorFlow Developer Certificate in 2021 Zero to Mastery 19.9 GB

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【影视】 GetFreeCourses.Co-Udemy-Tensorflow 2.0 Deep Learning and Artificial Intelligence

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18. Setting up your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.mp4 189.7 MB
18. Setting up your Environment (FAQ by Student Request)/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 175.4 MB
18. Setting up your Environment (FAQ by Student Request)/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 157.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 130.1 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 113.4 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 110.7 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 110.1 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 103.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 94.5 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 91.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 87.0 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 84.5 MB
4. Feedforward Artificial Neural Networks/5. Activation Functions.mp4 84.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/9. GRU and LSTM (pt 1).mp4 83.7 MB
5. Convolutional Neural Networks/1. What is Convolution (part 1).mp4 83.6 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 83.6 MB
10. GANs (Generative Adversarial Networks)/2. GAN Code.mp4 82.1 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 80.6 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. Beginner's Coding Tips.mp4 79.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 77.7 MB

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【影视】 [CourseClub.NET] Packtpub - Real-World Machine Learning Projects Using TensorFlow

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05.Traffic Sign Classifier/0502.Implementing Traffic Sign Classifier.mp4 132.1 MB
01.Getting Started with TensorFlow/0104.Warming Up Examples.mp4 95.0 MB
04.Anomaly Detection Algorithm/0402.Server Computer's Behavior.mp4 75.4 MB
03.Linear Regression with Multi Variable/0303.Problem Solution.mp4 69.3 MB
02.Linear Regression with One Variable/0203.Problem Statement and Solution.mp4 55.0 MB
02.Linear Regression with One Variable/0201.What Is Machine Learning.mp4 19.8 MB
02.Linear Regression with One Variable/0202.Model Representation and Gradient Descent.mp4 15.0 MB
01.Getting Started with TensorFlow/0103.Installing TensorFlow.mp4 14.6 MB
01.Getting Started with TensorFlow/0101.The Course Overview.mp4 12.7 MB
01.Getting Started with TensorFlow/0102.Installing and Preparing the Environment.mp4 10.2 MB
04.Anomaly Detection Algorithm/0401.What Is Anomaly Detection.mp4 5.5 MB
05.Traffic Sign Classifier/0501.Introduction to Traffic Sign Classifier.mp4 3.7 MB
03.Linear Regression with Multi Variable/0301.Model Representation.mp4 2.2 MB
03.Linear Regression with Multi Variable/0302.Problem Statement.mp4 1.5 MB
Exercise Files/exercise_files.zip 208.3 kB
[CourseClub.NET].url 123 Bytes
[DesireCourse.Com].url 51 Bytes

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【影视】 [DesireCourse.Net] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence

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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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【影视】 [FreeCourseSite.com] Udemy - TensorFlow Developer Certificate in 2022 Zero to Mastery

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[FreeCourseSite.com] Udemy - TensorFlow Developer Certificate in 2022 Zero to Mastery 29.1 GB

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【影视】 [FreeCourseSite.com] Udemy - Master Deep Learning with TensorFlow in Python

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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
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
2. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 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
13. Business case/4. Preprocessing the data.mp4 36.0 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
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4 34.2 MB
13. Business case/6. Create a class for batching.mp4 29.0 MB
14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.mp4 28.0 MB
14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.mp4 25.2 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 24.4 MB
14. Appendix Linear Algebra Fundamentals/5. Tensors.mp4 23.6 MB
12. The MNIST example/9. Discuss the results and test.mp4 23.0 MB
4. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.mp4 21.8 MB
13. Business case/7. Outlining the model.mp4 20.4 MB
12. The MNIST example/4. Outlining the model.mp4 19.3 MB

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【影视】 [DesireCourse.Net] Udemy - Master Deep Learning with TensorFlow in Python

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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
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
2. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 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
13. Business case/4. Preprocessing the data.mp4 36.0 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
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4 34.2 MB
13. Business case/6. Create a class for batching.mp4 29.0 MB
14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.mp4 28.0 MB
14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.mp4 25.2 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 24.4 MB
14. Appendix Linear Algebra Fundamentals/5. Tensors.mp4 23.6 MB
12. The MNIST example/9. Discuss the results and test.mp4 23.0 MB
4. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.mp4 21.8 MB
13. Business case/7. Outlining the model.mp4 20.4 MB
12. The MNIST example/4. Outlining the model.mp4 19.3 MB

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【影视】 [DesireCourse.Net] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence

收录时间:2020-03-28 文档个数:246 文档大小:7.2 GB 最近下载:2025-02-08 人气:284 磁力链接

18. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4 203.4 MB
18. Appendix FAQ/3. 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
18. Appendix FAQ/11. What order should I take your courses in (part 2).mp4 128.6 MB
18. Appendix FAQ/4. 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
18. Appendix FAQ/10. 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
5. Convolutional Neural Networks/1. What is Convolution (part 1).mp4 87.6 MB

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【影视】 [GigaCourse.Com] Udemy - TensorFlow 2.0 Practical Advanced

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01 - INTRODUCTION AND COURSE OUTLINE/007 Whats New in TensorFlow 2.0.mp4 229.6 MB
05 - DEEP DREAM/008 Deep Dream Coding P5.mp4 221.2 MB
05 - DEEP DREAM/001 What is Deep Dream.mp4 203.4 MB
05 - DEEP DREAM/002 How does DeepDream Algo work.mp4 162.6 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/001 ANN and CNN - Part 1.mp4 149.3 MB
04 - AUTOENCODERS/013 Autoencoders Project 2 - Coding P2.mp4 147.5 MB
04 - AUTOENCODERS/001 Autoencoders intuition.mp4 124.4 MB
04 - AUTOENCODERS/20087012-traffic-signs-data.zip 121.4 MB
03 - TRANSFER LEARNING (TF HUB)/006 Transfer Learning Project 1 - Coding P2.mp4 114.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/010 Project 1 - Solution Part 2.mp4 106.3 MB
06 - GANs/010 GANS Project 1 P5.mp4 102.1 MB
08 - TENSORFLOW SERVING AND TENSORBOARD/003 TF Serving Coding Part 3.mp4 102.1 MB
05 - DEEP DREAM/007 Deep Dream Coding P4.mp4 101.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/007 ANN and CNN - Part 7.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/006 Vanishing Gradient Problem.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/007 Long Short Term Memory LSTM.mp4 96.7 MB
01 - INTRODUCTION AND COURSE OUTLINE/004 ML, AI and DL.mp4 96.2 MB
06 - GANs/001 GANS intuition.mp4 95.4 MB
03 - TRANSFER LEARNING (TF HUB)/005 Transfer Learning Project 1 - Coding P1.mp4 93.8 MB
03 - TRANSFER LEARNING (TF HUB)/007 Transfer Learning Project 1 - Coding P3.mp4 92.6 MB

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【影视】 [ TutGee.com ] Linkedin - TensorFlow - Working with NLP

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~Get Your Files Here !/4. Transformers and BERT/017. Fine-tuning BERT.mp4 72.3 MB
~Get Your Files Here !/4. Transformers and BERT/013. BERT model and tokenization.mp4 32.4 MB
~Get Your Files Here !/3. BERT and Transfer Learning/009. Bias in BERT and GPT.mp4 30.5 MB
~Get Your Files Here !/2. NLP and Transformers/006. Transformers, their use, and history.mp4 28.7 MB
~Get Your Files Here !/3. BERT and Transfer Learning/011. Transfer learning.mp4 25.7 MB
~Get Your Files Here !/2. NLP and Transformers/004. What is NLP.mp4 24.9 MB
~Get Your Files Here !/1. Introduction/003. What is TensorFlow.mp4 22.6 MB
~Get Your Files Here !/4. Transformers and BERT/014. Tokenizers.mp4 20.6 MB
~Get Your Files Here !/2. NLP and Transformers/005. Transformers for NLP.mp4 19.4 MB
~Get Your Files Here !/3. BERT and Transfer Learning/010. How was BERT trained.mp4 18.9 MB
~Get Your Files Here !/4. Transformers and BERT/015. Self-attention.mp4 17.9 MB
~Get Your Files Here !/2. NLP and Transformers/008. Solution NLP model size.mp4 14.2 MB
~Get Your Files Here !/4. Transformers and BERT/012. Transformer Architecture overview.mp4 13.7 MB
~Get Your Files Here !/5. Conclusion/018. Next steps.mp4 7.7 MB
~Get Your Files Here !/4. Transformers and BERT/016. Multi-head attention and feedforward network.mp4 7.7 MB
~Get Your Files Here !/1. Introduction/001. Why TensorFlow.mp4 7.2 MB
~Get Your Files Here !/2. NLP and Transformers/007. Challenge NLP model size.mp4 7.0 MB
~Get Your Files Here !/1. Introduction/002. What you should know.mp4 4.6 MB
~Get Your Files Here !/4. Transformers and BERT/017. Fine-tuning BERT.en.srt 13.6 kB
~Get Your Files Here !/4. Transformers and BERT/013. BERT model and tokenization.en.srt 6.5 kB

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【影视】 [FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced

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01 - INTRODUCTION AND COURSE OUTLINE/007 Whats New in TensorFlow 2.0.mp4 229.6 MB
05 - DEEP DREAM/008 Deep Dream Coding P5.mp4 221.2 MB
05 - DEEP DREAM/001 What is Deep Dream.mp4 203.4 MB
05 - DEEP DREAM/002 How does DeepDream Algo work.mp4 162.6 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/001 ANN and CNN - Part 1.mp4 149.3 MB
04 - AUTOENCODERS/013 Autoencoders Project 2 - Coding P2.mp4 147.5 MB
04 - AUTOENCODERS/001 Autoencoders intuition.mp4 124.4 MB
04 - AUTOENCODERS/20087012-traffic-signs-data.zip 121.4 MB
03 - TRANSFER LEARNING (TF HUB)/006 Transfer Learning Project 1 - Coding P2.mp4 114.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/010 Project 1 - Solution Part 2.mp4 106.3 MB
06 - GANs/010 GANS Project 1 P5.mp4 102.1 MB
08 - TENSORFLOW SERVING AND TENSORBOARD/003 TF Serving Coding Part 3.mp4 102.1 MB
05 - DEEP DREAM/007 Deep Dream Coding P4.mp4 101.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/007 ANN and CNN - Part 7.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/006 Vanishing Gradient Problem.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/007 Long Short Term Memory LSTM.mp4 96.7 MB
01 - INTRODUCTION AND COURSE OUTLINE/004 ML, AI and DL.mp4 96.2 MB
06 - GANs/001 GANS intuition.mp4 95.4 MB
03 - TRANSFER LEARNING (TF HUB)/005 Transfer Learning Project 1 - Coding P1.mp4 93.8 MB
03 - TRANSFER LEARNING (TF HUB)/007 Transfer Learning Project 1 - Coding P3.mp4 92.6 MB

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【影视】 [ CourseWikia.com ] PluralSight - TensorFlow Developer Certificate - Time Series, Sequences, and Predictions

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~Get Your Files Here !/2. Understanding and Preparing Time Series Data/7. Demo - Techniques for Identifying and Reducing Sequenc.mp4 15.0 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/5. Demo - Predictive Modelling with TensorFl.mp4 14.8 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/4. Demo - Implementing Model Training and Evaluation.mp4 12.5 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/5. Demo - Time Series Data Preparation.mp4 12.1 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/2. Defining Time Series and Sequences.mp4 12.0 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/8. Demo - Implementing a CNN for Time Series Prediction.mp4 10.4 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/3. Demo - Time Series Visualization.mp4 9.5 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/6. Demo - Building an RNN for Time Series Prediction.mp4 9.1 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/3. Demo - Comparing Trailing Windows.mp4 8.9 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/1. Intended Outcome and Prerequisites.mp4 6.0 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/3. Techniques for Model Training and Hyperparameter Tuning.mp4 5.9 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/4. Data Preparation Techniques for Time Series Learning.mp4 5.9 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/1. Overview of Error Metrics.mp4 5.9 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/6. Advanced Forecasting Techniques with Tens.mp4 5.5 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/7. Implementing Convolutional Neural Networks (CNNs).mp4 5.4 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/1. Understanding Data Windowing in Time Seri.mp4 5.3 MB
~Get Your Files Here !/1. Course Overview/1. Course Overview.mp4 5.1 MB
~Get Your Files Here !/3. Training and Evaluating Time Series Models/5. Implementing Recurrent Neural Networks (RNNs).mp4 4.9 MB
~Get Your Files Here !/2. Understanding and Preparing Time Series Data/6. Addressing Sequence Bias in Time Series Analysis.mp4 4.7 MB
~Get Your Files Here !/4. Implementing Advanced Techniques for Time Series Analysis/4. Leveraging TensorFlow for Forecasting.mp4 3.9 MB

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Chapter 7 - Recurrent Neural Networks and LSTM/35. Writing Music a la Bach.mp4 47.1 MB
Chapter 1 - Exploring and Transforming data/04. Basic Tensor Methods.mp4 38.7 MB
Chapter 4 - Logistic Regression/18. Univariate Logistic Regression.mp4 33.2 MB
Chapter 1 - Exploring and Transforming data/02. TensorFlow's Main Data Structure Tensors.mp4 28.5 MB
Chapter 3 - Linear Regression/14. Univariate Linear Regression.mp4 26.5 MB
Chapter 1 - Exploring and Transforming data/05. How TensorBoard Works.mp4 25.8 MB
Chapter 1 - Exploring and Transforming data/06. Reading Information from Disk.mp4 22.9 MB
Chapter 3 - Linear Regression/15. Multivariate Linear Regression.mp4 22.6 MB
Chapter 2 - Clustering/10. Project 1 k-Means Clustering on Synthetic Datasetsets.mp4 20.4 MB
Chapter 2 - Clustering/09. k-Nearest Neighbor.mp4 19.8 MB
Chapter 1 - Exploring and Transforming data/01. The Course Overview.mp4 19.5 MB
Chapter 6 - Convolutional Neural Networks/25. Applying Convolution in TensorFlow.mp4 18.8 MB
Chapter 6 - Convolutional Neural Networks/29. MNIST Digit Classification.mp4 18.7 MB
Chapter 1 - Exploring and Transforming data/03. Handling the Computing Workflow TensorFlow's Data Flow Graph.mp4 17.0 MB
Chapter 5 - Simple FeedForward Neural Networks/22. Second Project Modeling Cars Fuel Efficiency with Non-Linear.mp4 16.4 MB
Chapter 8 - Deep Neural Networks/40. Painting with Style VGG Style Transfer.mp4 16.2 MB
Chapter 7 - Recurrent Neural Networks and LSTM/34. Univariate Time Series Prediction with Energy Consumption Data.mp4 14.5 MB
Chapter 9 - Library Installation And Additional Tips/42. mac OS Installation.mp4 14.3 MB
Chapter 5 - Simple FeedForward Neural Networks/21. First Project Non-Linear Synthetic Function Regression.mp4 14.3 MB
Chapter 5 - Simple FeedForward Neural Networks/20. Preliminary Concepts.mp4 14.0 MB

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【影视】 [Tutorialsplanet.NET] Udemy - Deep Learning with TensorFlow 2.0 [2020]

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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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13. Business case/4. Preprocessing the data.mp4 81.2 MB
14. Conclusion/3. An overview of CNNs.mp4 75.4 MB
6. Deep nets overview/3. Really understand deep nets.mp4 61.0 MB
2. Neural networks Intro/11. One-parameter gradient descent.mp4 59.1 MB
6. Deep nets overview/7. Backpropagation.mp4 55.3 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 54.6 MB
2. Neural networks Intro/12. N-parameter gradient descent.mp4 52.5 MB
1. Introduction/2. What does the course cover.mp4 51.6 MB
14. Conclusion/1. Summary.mp4 50.9 MB
4. Minimal example/4. Training the model.mp4 48.8 MB
13. Business case/3. Balancing the dataset.mp4 46.8 MB
13. Business case/7. Setting an early stopping mechanism.mp4 44.7 MB
2. Neural networks Intro/1. Introduction to neural networks.mp4 44.6 MB
2. Neural networks Intro/6. The linear model. Multiple inputs and multiple outputs.mp4 44.3 MB
14. Conclusion/5. Non-NN approaches.mp4 43.9 MB
5. Introduction to TensorFlow 2/1. TensorFlow outline.mp4 43.2 MB
12. Deeper example/8. Learning.mp4 42.9 MB
2. Neural networks Intro/3. Types of machine learning.mp4 42.8 MB
11. Preprocessing/3. Standardization.mp4 42.3 MB
6. Deep nets overview/4. Why do we need non-linearities.mp4 39.8 MB

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01 Course Overview Installs and Setup/002 Course Setup and Installation.mp4 159.8 MB
13 Deployment/114 Flask Front End.mp4 156.9 MB
09 Recurrent Neural Networks - RNNs/088 Bonus - Multivariate Time Series - RNN and LSTMs.mp4 156.6 MB
09 Recurrent Neural Networks - RNNs/087 RNN Exercise - Solutions.mp4 155.3 MB
07 Basic Artificial Neural Networks - ANNs/057 Tensorboard.mp4 151.2 MB
07 Basic Artificial Neural Networks - ANNs/050 Keras Project Solutions - Exploratory Data Analysis.mp4 150.6 MB
07 Basic Artificial Neural Networks - ANNs/042 Keras Regression Code Along - Exploratory Data Analysis.mp4 143.7 MB
12 Generative Adversarial Networks/106 Creating a GAN - Part Three - Model Training.mp4 138.0 MB
09 Recurrent Neural Networks - RNNs/085 RNN on a Time Series - Part Two.mp4 137.4 MB
13 Deployment/115 Live Deployment to the Web.mp4 132.7 MB
07 Basic Artificial Neural Networks - ANNs/053 Keras Project Solutions - Categorical Data.mp4 131.1 MB
11 AutoEncoders/098 Autoencoder for Dimensionality Reduction.mp4 123.2 MB
07 Basic Artificial Neural Networks - ANNs/047 Keras Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
01 Course Overview Installs and Setup/002 FINAL-TF2-FILES.zip 104.1 MB
01 Course Overview Installs and Setup/003 FINAL-TF2-FILES.zip 104.1 MB
08 Convolutional Neural Networks - CNNs/064 CNN on MNIST - Part Two - Creating and Training the Model.mp4 103.7 MB
07 Basic Artificial Neural Networks - ANNs/051 Keras Project Solutions - Dealing with Missing Data.mp4 101.5 MB
11 AutoEncoders/099 Autoencoder for Images - Part One.mp4 98.7 MB
04 Pandas Crash Course/017 Data Input and Output.mp4 98.0 MB
05 Visualization Crash Course/022 Seaborn Basics.mp4 96.3 MB

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01 - INTRODUCTION AND COURSE OUTLINE/007 Whats New in TensorFlow 2.0.mp4 229.6 MB
05 - DEEP DREAM/008 Deep Dream Coding P5.mp4 221.2 MB
05 - DEEP DREAM/001 What is Deep Dream.mp4 203.4 MB
05 - DEEP DREAM/002 How does DeepDream Algo work.mp4 162.6 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/001 ANN and CNN - Part 1.mp4 149.3 MB
04 - AUTOENCODERS/013 Autoencoders Project 2 - Coding P2.mp4 147.5 MB
04 - AUTOENCODERS/001 Autoencoders intuition.mp4 124.4 MB
04 - AUTOENCODERS/20087012-traffic-signs-data.zip 121.4 MB
03 - TRANSFER LEARNING (TF HUB)/006 Transfer Learning Project 1 - Coding P2.mp4 114.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/010 Project 1 - Solution Part 2.mp4 106.3 MB
06 - GANs/010 GANS Project 1 P5.mp4 102.1 MB
08 - TENSORFLOW SERVING AND TENSORBOARD/003 TF Serving Coding Part 3.mp4 102.1 MB
05 - DEEP DREAM/007 Deep Dream Coding P4.mp4 101.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/007 ANN and CNN - Part 7.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/006 Vanishing Gradient Problem.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/007 Long Short Term Memory LSTM.mp4 96.7 MB
01 - INTRODUCTION AND COURSE OUTLINE/004 ML, AI and DL.mp4 96.2 MB
06 - GANs/001 GANS intuition.mp4 95.4 MB
03 - TRANSFER LEARNING (TF HUB)/005 Transfer Learning Project 1 - Coding P1.mp4 93.8 MB
03 - TRANSFER LEARNING (TF HUB)/007 Transfer Learning Project 1 - Coding P3.mp4 92.6 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
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13. Business case/8. Learning and interpreting the result.mp4 32.7 MB

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