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1. CNN Section Overview.mp4
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1. Course Overview.mp4
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1. GANs Overview.mp4
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1. Introduction to ANN Section.mp4
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1. Introduction to Autoencoders.mp4
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1. Introduction to Deployment.mp4
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1. Introduction to NLP Section.mp4
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1. Introduction to NumPy.mp4
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1. Introduction to Pandas.mp4
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1. Introduction to Python Visualization.mp4
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1. PLEASE WATCH COURSE OVERVIEW LECTURE.html
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204 B
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1. RNN Section Overview.mp4
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1. What is Machine Learning.mp4
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1. What is Machine Learning.srt
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10. CNN on CIFAR-10 - Part Two - Evaluating the Model.mp4
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10. CNN on CIFAR-10 - Part Two - Evaluating the Model.srt
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10. Keras Syntax Basics - Part Two - Creating and Training the Model.mp4
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84.6 MB
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10. Keras Syntax Basics - Part Two - Creating and Training the Model.srt
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10. Pandas Exercises - Solutions.mp4
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51.5 MB
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10. Pandas Exercises - Solutions.srt
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10. RNN on a Time Series - Part One.mp4
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45 MB
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10. RNN on a Time Series - Part One.srt
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11. Downloading Data Set for Real Image Lectures.mp4
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11. Keras Syntax Basics - Part Three - Model Evaluation.mp4
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11. RNN on a Time Series - Part Two.mp4
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11.1 Direct Link to Download cell_images.zip (Note You can't preview a zip file) Just download it..html
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102 B
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12. CNN on Real Image Files - Part One - Reading in the Data.mp4
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80.7 MB
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12. CNN on Real Image Files - Part One - Reading in the Data.srt
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12. Keras Regression Code Along - Exploratory Data Analysis.mp4
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12. Keras Regression Code Along - Exploratory Data Analysis.srt
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12. RNN Exercise.mp4
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12. RNN Exercise.srt
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13. CNN on Real Image Files - Part Two - Data Processing.mp4
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13. CNN on Real Image Files - Part Two - Data Processing.srt
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13. Keras Regression Code Along - Exploratory Data Analysis - Continued.mp4
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13. Keras Regression Code Along - Exploratory Data Analysis - Continued.srt
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13. RNN Exercise - Solutions.mp4
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13. RNN Exercise - Solutions.srt
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14. Bonus - Multivariate Time Series - RNN and LSTMs.mp4
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14. Bonus - Multivariate Time Series - RNN and LSTMs.srt
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14. CNN on Real Image Files - Part Three - Creating the Model.mp4
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14. CNN on Real Image Files - Part Three - Creating the Model.srt
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14. Keras Regression Code Along - Data Preprocessing and Creating a Model.mp4
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15. CNN on Real Image Files - Part Four - Evaluating the Model.mp4
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15. CNN on Real Image Files - Part Four - Evaluating the Model.srt
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15. Keras Regression Code Along - Model Evaluation and Predictions.mp4
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16. CNN Exercise Overview.mp4
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16. CNN Exercise Overview.srt
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16. Keras Classification Code Along - EDA and Preprocessing.mp4
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17. CNN Exercise Solutions.mp4
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56 MB
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17. CNN Exercise Solutions.srt
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17. Keras Classification - Dealing with Overfitting and Evaluation.mp4
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17. Keras Classification - Dealing with Overfitting and Evaluation.srt
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18. TensorFlow 2.0 Keras Project Options Overview.mp4
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18. TensorFlow 2.0 Keras Project Options Overview.srt
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19. TensorFlow 2.0 Keras Project Notebook Overview.mp4
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2. Autoencoder Basics.mp4
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2. Course Setup and Installation.mp4
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2. Creating a GAN - Part One- The Data.mp4
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2. Creating the Model.mp4
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2. Creating the Model.srt
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2. Image Filters and Kernels.mp4
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2. Matplotlib Basics.mp4
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41 MB
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2. NLP - Part One - The Data.mp4
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2. NLP - Part One - The Data.srt
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2. NumPy Arrays.mp4
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2. Pandas Series.mp4
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2. Perceptron Model.mp4
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2. Perceptron Model.srt
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2. RNN Basic Theory.mp4
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30 MB
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2. Supervised Learning Overview.mp4
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40 MB
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2. Supervised Learning Overview.srt
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2.1 FINAL_TF2_FILES.zip.zip
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99.3 MB
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2.2 requirements.txt.txt
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102 B
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20. Keras Project Solutions - Exploratory Data Analysis.mp4
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143.6 MB
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20. Keras Project Solutions - Exploratory Data Analysis.srt
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21. Keras Project Solutions - Dealing with Missing Data.mp4
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22. Keras Project Solutions - Dealing with Missing Data - Part Two.mp4
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23. Keras Project Solutions - Categorical Data.mp4
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125 MB
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24. Keras Project Solutions - Data PreProcessing.mp4
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25. Keras Project Solutions - Creating and Training a Model.mp4
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25. Keras Project Solutions - Creating and Training a Model.srt
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26. Keras Project Solutions - Model Evaluation.mp4
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26. Keras Project Solutions - Model Evaluation.srt
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27. Tensorboard.mp4
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27. Tensorboard.srt
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3. Autoencoder for Dimensionality Reduction.mp4
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3. Autoencoder for Dimensionality Reduction.srt
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3. Convolutional Layers.mp4
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3. Convolutional Layers.srt
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3. Creating a GAN - Part Two - The Model.mp4
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3. Creating a GAN - Part Two - The Model.srt
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3. FAQ - Frequently Asked Questions.html
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3. Model Prediction Function.mp4
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53 MB
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3. Model Prediction Function.srt
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3. NLP - Part Two - Text Processing.mp4
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3. Neural Networks.mp4
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3. Neural Networks.srt
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3. Numpy Index Selection.mp4
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3. Overfitting.mp4
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3. Overfitting.srt
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3. Pandas DataFrames - Part One.mp4
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3. Seaborn Basics.mp4
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91.8 MB
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3. Vanishing Gradients.mp4
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3.1 FINAL_TF2_FILES.zip.zip
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99.3 MB
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4. Activation Functions.mp4
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4. Activation Functions.srt
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4. Autoencoder for Images - Part One.mp4
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94.1 MB
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4. Creating a GAN - Part Three - Model Training.mp4
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131.6 MB
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4. Creating a GAN - Part Three - Model Training.srt
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4. Data Visualization Exercises.mp4
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22.8 MB
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4. Data Visualization Exercises.srt
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4. Evaluating Performance - Classification Error Metrics.mp4
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82.7 MB
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4. Evaluating Performance - Classification Error Metrics.srt
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4. LSTMS and GRU.mp4
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41.9 MB
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4. LSTMS and GRU.srt
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4. NLP - Part Three - Creating Batches.mp4
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81.7 MB
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4. NLP - Part Three - Creating Batches.srt
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4. NumPy Operations.mp4
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4. NumPy Operations.srt
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4. Pandas DataFrames - Part Two.mp4
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37 MB
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4. Pandas DataFrames - Part Two.srt
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4. Pooling Layers.mp4
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4. Pooling Layers.srt
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4. Running a Basic Flask Application.mp4
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62 MB
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4. Running a Basic Flask Application.srt
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4.1 Great Blog Post on Exploring LSTM Neurons.html
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102 B
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4.2 Famous Karpathy Blog Post.html
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102 B
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4.3 Wikipedia Article Describing LSTM Variants.html
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102 B
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4.4 How to choose between LSTM vs GRU.html
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102 B
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5. Autoencoder for Images - Part Two - Noise Removal.mp4
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5. DCGAN - Deep Convolutional Generative Adversarial Networks.mp4
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5. DCGAN - Deep Convolutional Generative Adversarial Networks.srt
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5. Data Visualization Exercises - Solutions.mp4
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5. Evaluating Performance - Regression Error Metrics.mp4
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5. Evaluating Performance - Regression Error Metrics.srt
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5. Flask Postman API.mp4
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69.1 MB
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5. Flask Postman API.srt
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5. MNIST Data Set Overview.mp4
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21.1 MB
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5. MNIST Data Set Overview.srt
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5. Multi-Class Classification Considerations.mp4
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5. Multi-Class Classification Considerations.srt
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5. NLP - Part Four - Creating the Model.mp4
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5. NLP - Part Four - Creating the Model.srt
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5. NumPy Exercises.mp4
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5. Pandas Missing Data.mp4
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5. RNN Batches.mp4
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32.7 MB
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5. RNN Batches.srt
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6. Autoencoder Exercise Overview.mp4
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33.9 MB
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6. Autoencoder Exercise Overview.srt
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6. CNN on MNIST - Part One - The Data.mp4
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59.8 MB
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6. CNN on MNIST - Part One - The Data.srt
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6. Cost Functions and Gradient Descent.mp4
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75.7 MB
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6. Cost Functions and Gradient Descent.srt
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27 KB
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6. Flask API - Using Requests Programmatically.mp4
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19.9 MB
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6. Flask API - Using Requests Programmatically.srt
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6. GroupBy Operations.mp4
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56.4 MB
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6. GroupBy Operations.srt
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6. NLP - Part Five - Training the Model.mp4
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65.3 MB
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6. NLP - Part Five - Training the Model.srt
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6. Numpy Exercises - Solutions.mp4
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48.6 MB
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6. Numpy Exercises - Solutions.srt
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6. RNN on a Sine Wave - The Data.mp4
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6. RNN on a Sine Wave - The Data.srt
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6. Unsupervised Learning.mp4
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18.8 MB
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6. Unsupervised Learning.srt
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7. Autoencoder Exercise - Solutions.mp4
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77.8 MB
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7. Autoencoder Exercise - Solutions.srt
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7. Backpropagation.mp4
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7. Backpropagation.srt
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7. CNN on MNIST - Part Two - Creating and Training the Model.mp4
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98.9 MB
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7. CNN on MNIST - Part Two - Creating and Training the Model.srt
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7. Flask Front End.mp4
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7. Flask Front End.srt
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7. NLP - Part Six - Generating Text.mp4
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7. Pandas Operations.mp4
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7. RNN on a Sine Wave - Batch Generator.mp4
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7. RNN on a Sine Wave - Batch Generator.srt
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7.1 Great walkthrough for BackPropagation!.html
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8. CNN on MNIST - Part Three - Model Evaluation.mp4
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8. Data Input and Output.mp4
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8. Live Deployment to the Web.mp4
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8. RNN on a Sine Wave - Creating the Model.mp4
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8. TensorFlow vs. Keras Explained.mp4
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9. CNN on CIFAR-10 - Part One - The Data.mp4
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9. Keras Syntax Basics - Part One - Preparing the Data.mp4
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9. Pandas Exercises.mp4
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9. RNN on a Sine Wave - LSTMs and Forecasting.mp4
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[FreeCourseWorld.Com].url
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![Udemy - Complete Tensorflow 2 and Keras Deep Learning Bootcamp [Desire Course]](/static/img/no-torrent-image.png "Udemy - Complete Tensorflow 2 and Keras Deep Learning Bootcamp [Desire Course]")
