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Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow

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A book by Aurélien Géron

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# Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition
 A book by Aurélien Géron

# Notebooks
### Chapter 1 - The Machine Learning Landscape

- [Predicting Life Satisfaction using GDP per capita.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C1_N1_Predicting%20Life%20Satisfaction%20using%20GDP%20per%20capita.ipynb)

### Chapter 2 - End-to-End Machine Learning Project

- [Predicting Housing Prices.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C2_N1_Predicting%20Housing%20Price.ipynb)

### Chapter 3 - Classification

- [Building Classifiers on MNIST.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C3_N1_Classification%20on%20MNIST.ipynb)

### Chapter 4 - Training Models

- [Linear, Polynomial, Logistic, and Softmax Regressions.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C4_N1_Linear%2C%20Polynomial%2C%20Logistic%2C%20and%20Softmax%20Regressions.ipynb)

### Chapter 5 - Support Vector Machines

- [Support Vector Machines.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C5_N1_Support%20Vector%20Machines.ipynb)

### Chapter 6 - Decision Trees

- [Decision Trees.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C6_N1_Decision%20Trees.ipynb)

### Chapter 7 - Ensemble Learning and Random Forests

- [Ensemble Learning and Random Forests.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C7_N1_Ensemble%20Learning%20and%20Random%20Forests.ipynb)

### Chapter 8 - Dimensionality Reduction

- [PCA, Kernel PCA, and LLE.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C8_N1_PCA%2C%20Kernel%20PCA%2C%20and%20LLE.ipynb)

### Chapter 9 - Unsupervised Learning Techniques

- [Clustering: K-Means and DBSCAN.ipynb]()
- [Gaussian Mixtures.ipynb]()

### Chapter 10 - Introduction to Artificial Neural Networks with Keras

- [Implementing MLP and Fine-Tuning NN Hyperparameters.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C10_N1_Implementing%20MLP%20and%20Fine-Tuning%20NN%20Hyperparameters.ipynb)

### Chapter 11 - Training Deep Neural Networks

- [Vanishing/Exploding Gradients Problems.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C11_N1_The%20Vanishing%20Exploding%20Gradients%20Problems.ipynb)
- [Transfer Learning and Unsupervised Pretraining.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C11_N2_Transfer%20Learning%20and%20Unsupervised%20Pretraining.ipynb)
- [Faster Optimizers.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C11_N3_Faster%20Optimizers.ipynb)
- [Popular Regularization Techniques for Large NNs.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C11_N4_Popular%20Regularization%20Techniques%20for%20Large%20NNs.ipynb)

### Chapter 12 - Custom Models and Training with TensorFlow

- [Tensors and Operations.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C12_N1_Tensors%20and%20Operations.ipynb)
- [Custom Models and Training.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C12_N2_Custom%20Models%20and%20Training.ipynb)

### Chapter 13 - Loading and Preprocessing with TensorFlow

- [Loading and Preprocessing Data.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C13_N1_Loading%20and%20Preprocessing%20Data.ipynb)

### Chapter 14 - Deep Computer Vision Using Convolutional Neural Networks

- [Deep Computer Vision Using CNNs.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C14_N1_Deep%20Computer%20Vision%20Using%20CNNs.ipynb)

### Chapter 15 - Processing Sequences Using RNNs and CNNs

- [Processing Sequences Using RNNs and CNNs.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C15_N1_Processing%20Sequences%20using%20RNNs%20and%20CNNs.ipynb)

### Chapter 16 - Natural Language Processing with RNNs and Attention

- [NLP with RNNs and Attention.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C16_N1_NLP%20with%20RNNs%20and%20Attention.ipynb)

### Chapter 17 - Representation Learning and Generative Learning Using Autoencoders and GANs

- [Autoencoders and GANs.ipynb](https://github.com/Andrew-Ng-s-number-one-fan/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow/blob/master/Notebooks/C17_N1_Autoencoders%20and%20GANs.ipynb)

### Chapter 18 - Reinforcement Learning

- Reinforcement Learning.ipynb (To be updated)

### Chapter 19 - Training and Deploying TensorFlow Models at Scale

- Training and Deploying.ipynb (To be updated)

Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow

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