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[DesireCourse Net] Udemy - Complete Tensorflow 2 and Keras Deep Learning Bootcamp
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Name:[DesireCourse Net] Udemy - Complete Tensorflow 2 and Keras Deep Learning Bootcamp
Infohash: 5EA101C36BADAE3708E0F8B86787615D5A5FF1BA
Total Size: 6.74 GB
Magnet: Magnet Download
Seeds: 1
Leechers: 1
Stream: Watch Full Movies @ LimeMovies
Last Updated: 2026-01-23 03:52:58 (Update Now)
Torrent added: 2020-01-17 05:01:00
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Torrent Files List
1. Course Overview, Installs, and Setup (Size: 6.74 GB) (Files: 240)
1. Course Overview, Installs, and Setup
1. Course Overview.mp4
1. Course Overview.srt
2. Course Setup and Installation.mp4
2. Course Setup and Installation.srt
2.1 FINAL_TF2_FILES.zip.zip
2.2 requirements.txt.txt
3. FAQ - Frequently Asked Questions.html
3.1 FINAL_TF2_FILES.zip.zip
10. Natural Language Processing
1. Introduction to NLP Section.mp4
1. Introduction to NLP Section.srt
2. NLP - Part One - The Data.mp4
2. NLP - Part One - The Data.srt
3. NLP - Part Two - Text Processing.mp4
3. NLP - Part Two - Text Processing.srt
4. NLP - Part Three - Creating Batches.mp4
4. NLP - Part Three - Creating Batches.srt
5. NLP - Part Four - Creating the Model.mp4
5. NLP - Part Four - Creating the Model.srt
6. NLP - Part Five - Training the Model.mp4
6. NLP - Part Five - Training the Model.srt
7. NLP - Part Six - Generating Text.mp4
7. NLP - Part Six - Generating Text.srt
11. AutoEncoders
1. Introduction to Autoencoders.mp4
2. Autoencoder Basics.mp4
2. Autoencoder Basics.srt
3. Autoencoder for Dimensionality Reduction.mp4
3. Autoencoder for Dimensionality Reduction.srt
4. Autoencoder for Images - Part One.mp4
4. Autoencoder for Images - Part One.srt
5. Autoencoder for Images - Part Two - Noise Removal.mp4
5. Autoencoder for Images - Part Two - Noise Removal.srt
6. Autoencoder Exercise Overview.mp4
6. Autoencoder Exercise Overview.srt
7. Autoencoder Exercise - Solutions.mp4
7. Autoencoder Exercise - Solutions.srt
12. Generative Adversarial Networks
1. GANs Overview.mp4
1. GANs Overview.srt
2. Creating a GAN - Part One- The Data.mp4
2. Creating a GAN - Part One- The Data.srt
3. Creating a GAN - Part Two - The Model.mp4
3. Creating a GAN - Part Two - The Model.srt
4. Creating a GAN - Part Three - Model Training.mp4
4. Creating a GAN - Part Three - Model Training.srt
5. DCGAN - Deep Convolutional Generative Adversarial Networks.mp4
5. DCGAN - Deep Convolutional Generative Adversarial Networks.srt
13. Deployment
1. Introduction to Deployment.mp4
1. Introduction to Deployment.srt
2. Creating the Model.mp4
2. Creating the Model.srt
3. Model Prediction Function.mp4
3. Model Prediction Function.srt
4. Running a Basic Flask Application.mp4
4. Running a Basic Flask Application.srt
5. Flask Postman API.mp4
5. Flask Postman API.srt
6. Flask API - Using Requests Programmatically.mp4
6. Flask API - Using Requests Programmatically.srt
7. Flask Front End.mp4
7. Flask Front End.srt
8. Live Deployment to the Web.mp4
8. Live Deployment to the Web.srt
2. COURSE OVERVIEW CONFIRMATION
1. PLEASE WATCH COURSE OVERVIEW LECTURE.html
3. NumPy Crash Course
1. Introduction to NumPy.mp4
1. Introduction to NumPy.srt
2. NumPy Arrays.mp4
2. NumPy Arrays.srt
3. Numpy Index Selection.mp4
3. Numpy Index Selection.srt
4. NumPy Operations.mp4
4. NumPy Operations.srt
5. NumPy Exercises.mp4
5. NumPy Exercises.srt
6. Numpy Exercises - Solutions.mp4
6. Numpy Exercises - Solutions.srt
4. Pandas Crash Course
1. Introduction to Pandas.mp4
1. Introduction to Pandas.srt
10. Pandas Exercises - Solutions.mp4
10. Pandas Exercises - Solutions.srt
2. Pandas Series.mp4
2. Pandas Series.srt
3. Pandas DataFrames - Part One.mp4
3. Pandas DataFrames - Part One.srt
4. Pandas DataFrames - Part Two.mp4
4. Pandas DataFrames - Part Two.srt
5. Pandas Missing Data.mp4
5. Pandas Missing Data.srt
6. GroupBy Operations.mp4
6. GroupBy Operations.srt
7. Pandas Operations.mp4
7. Pandas Operations.srt
8. Data Input and Output.mp4
8. Data Input and Output.srt
9. Pandas Exercises.mp4
9. Pandas Exercises.srt
5. Visualization Crash Course
1. Introduction to Python Visualization.mp4
1. Introduction to Python Visualization.srt
2. Matplotlib Basics.mp4
2. Matplotlib Basics.srt
3. Seaborn Basics.mp4
3. Seaborn Basics.srt
4. Data Visualization Exercises.mp4
4. Data Visualization Exercises.srt
5. Data Visualization Exercises - Solutions.mp4
5. Data Visualization Exercises - Solutions.srt
6. Machine Learning Concepts Overview
1. What is Machine Learning.mp4
1. What is Machine Learning.srt
2. Supervised Learning Overview.mp4
2. Supervised Learning Overview.srt
3. Overfitting.mp4
3. Overfitting.srt
4. Evaluating Performance - Classification Error Metrics.mp4
4. Evaluating Performance - Classification Error Metrics.srt
5. Evaluating Performance - Regression Error Metrics.mp4
5. Evaluating Performance - Regression Error Metrics.srt
6. Unsupervised Learning.mp4
6. Unsupervised Learning.srt
7. Basic Artificial Neural Networks - ANNs
1. Introduction to ANN Section.mp4
1. Introduction to ANN Section.srt
10. Keras Syntax Basics - Part Two - Creating and Training the Model.mp4
10. Keras Syntax Basics - Part Two - Creating and Training the Model.srt
11. Keras Syntax Basics - Part Three - Model Evaluation.mp4
11. Keras Syntax Basics - Part Three - Model Evaluation.srt
12. Keras Regression Code Along - Exploratory Data Analysis.mp4
12. Keras Regression Code Along - Exploratory Data Analysis.srt
13. Keras Regression Code Along - Exploratory Data Analysis - Continued.mp4
13. Keras Regression Code Along - Exploratory Data Analysis - Continued.srt
14. Keras Regression Code Along - Data Preprocessing and Creating a Model.mp4
14. Keras Regression Code Along - Data Preprocessing and Creating a Model.srt
15. Keras Regression Code Along - Model Evaluation and Predictions.mp4
15. Keras Regression Code Along - Model Evaluation and Predictions.srt
16. Keras Classification Code Along - EDA and Preprocessing.mp4
16. Keras Classification Code Along - EDA and Preprocessing.srt
17. Keras Classification - Dealing with Overfitting and Evaluation.mp4
17. Keras Classification - Dealing with Overfitting and Evaluation.srt
18. TensorFlow 2.0 Keras Project Options Overview.mp4
18. TensorFlow 2.0 Keras Project Options Overview.srt
19. TensorFlow 2.0 Keras Project Notebook Overview.mp4
19. TensorFlow 2.0 Keras Project Notebook Overview.srt
2. Perceptron Model.mp4
2. Perceptron Model.srt
20. Keras Project Solutions - Exploratory Data Analysis.mp4
20. Keras Project Solutions - Exploratory Data Analysis.srt
21. Keras Project Solutions - Dealing with Missing Data.mp4
21. Keras Project Solutions - Dealing with Missing Data.srt
22. Keras Project Solutions - Dealing with Missing Data - Part Two.mp4
22. Keras Project Solutions - Dealing with Missing Data - Part Two.srt
23. Keras Project Solutions - Categorical Data.mp4
23. Keras Project Solutions - Categorical Data.srt
24. Keras Project Solutions - Data PreProcessing.mp4
24. Keras Project Solutions - Data PreProcessing.srt
25. Keras Project Solutions - Creating and Training a Model.mp4
25. Keras Project Solutions - Creating and Training a Model.srt
26. Keras Project Solutions - Model Evaluation.mp4
26. Keras Project Solutions - Model Evaluation.srt
27. Tensorboard.mp4
27. Tensorboard.srt
3. Neural Networks.mp4
3. Neural Networks.srt
4. Activation Functions.mp4
4. Activation Functions.srt
5. Multi-Class Classification Considerations.mp4
5. Multi-Class Classification Considerations.srt
6. Cost Functions and Gradient Descent.mp4
6. Cost Functions and Gradient Descent.srt
7. Backpropagation.mp4
7. Backpropagation.srt
7.1 Great walkthrough for BackPropagation!.html
8. TensorFlow vs. Keras Explained.mp4
8. TensorFlow vs. Keras Explained.srt
9. Keras Syntax Basics - Part One - Preparing the Data.mp4
9. Keras Syntax Basics - Part One - Preparing the Data.srt
8. Convolutional Neural Networks - CNNs
1. CNN Section Overview.mp4
1. CNN Section Overview.srt
10. CNN on CIFAR-10 - Part Two - Evaluating the Model.mp4
10. CNN on CIFAR-10 - Part Two - Evaluating the Model.srt
11. Downloading Data Set for Real Image Lectures.mp4
11. Downloading Data Set for Real Image Lectures.srt
11.1 Direct Link to Download cell_images.zip (Note You can't preview a zip file) Just download it..html
12. CNN on Real Image Files - Part One - Reading in the Data.mp4
12. CNN on Real Image Files - Part One - Reading in the Data.srt
13. CNN on Real Image Files - Part Two - Data Processing.mp4
13. CNN on Real Image Files - Part Two - Data Processing.srt
14. CNN on Real Image Files - Part Three - Creating the Model.mp4
14. CNN on Real Image Files - Part Three - Creating the Model.srt
15. CNN on Real Image Files - Part Four - Evaluating the Model.mp4
15. CNN on Real Image Files - Part Four - Evaluating the Model.srt
16. CNN Exercise Overview.mp4
16. CNN Exercise Overview.srt
17. CNN Exercise Solutions.mp4
17. CNN Exercise Solutions.srt
2. Image Filters and Kernels.mp4
2. Image Filters and Kernels.srt
3. Convolutional Layers.mp4
3. Convolutional Layers.srt
4. Pooling Layers.mp4
4. Pooling Layers.srt
5. MNIST Data Set Overview.mp4
5. MNIST Data Set Overview.srt
6. CNN on MNIST - Part One - The Data.mp4
6. CNN on MNIST - Part One - The Data.srt
7. CNN on MNIST - Part Two - Creating and Training the Model.mp4
7. CNN on MNIST - Part Two - Creating and Training the Model.srt
8. CNN on MNIST - Part Three - Model Evaluation.mp4
8. CNN on MNIST - Part Three - Model Evaluation.srt
9. CNN on CIFAR-10 - Part One - The Data.mp4
9. CNN on CIFAR-10 - Part One - The Data.srt
9. Recurrent Neural Networks - RNNs
1. RNN Section Overview.mp4
1. RNN Section Overview.srt
10. RNN on a Time Series - Part One.mp4
10. RNN on a Time Series - Part One.srt
11. RNN on a Time Series - Part Two.mp4
11. RNN on a Time Series - Part Two.srt
12. RNN Exercise.mp4
12. RNN Exercise.srt
13. RNN Exercise - Solutions.mp4
13. RNN Exercise - Solutions.srt
14. Bonus - Multivariate Time Series - RNN and LSTMs.mp4
14. Bonus - Multivariate Time Series - RNN and LSTMs.srt
2. RNN Basic Theory.mp4
3. Vanishing Gradients.mp4
3. Vanishing Gradients.srt
4. LSTMS and GRU.mp4
4. LSTMS and GRU.srt
4.1 Great Blog Post on Exploring LSTM Neurons.html
4.2 Famous Karpathy Blog Post.html
4.3 Wikipedia Article Describing LSTM Variants.html
4.4 How to choose between LSTM vs GRU.html
5. RNN Batches.mp4
5. RNN Batches.srt
6. RNN on a Sine Wave - The Data.mp4
6. RNN on a Sine Wave - The Data.srt
7. RNN on a Sine Wave - Batch Generator.mp4
7. RNN on a Sine Wave - Batch Generator.srt
8. RNN on a Sine Wave - Creating the Model.mp4
8. RNN on a Sine Wave - Creating the Model.srt
9. RNN on a Sine Wave - LSTMs and Forecasting.mp4
9. RNN on a Sine Wave - LSTMs and Forecasting.srt
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