readme.md

Hands On ML Projects

Implementations and exercises from Hands on Machine Learning with Scikit-Learn, Keras, and Tensorflow by Aurélien Géron.

Chapter 3

• MNIST dataset classifier using KNN
• Titanic dataset classifier using Random Forests
• Spam filter using SVM classifier

Chapter 4

• Exercises

Chapter 5

• MNIST dataset classifier using SVM classifier
• Linear vs. non-linear SVM classifiers
• Exercises

Chapter 6

• Moons dataset Decision Tree classifier
• Exercises

Chapter 7

• MNIST dataset ensemble classifier
• Exercises

Chapter 8

• MNIST dataset dimensionality reduction with t-SNE, PCA, Locally Linear Embedding, and Multidimensional Scaling
• Exercises

Chapter 9

• Olivetti Faces dataset unsupervised learning with K-Means and Bayesian Gaussian Mixture Models
• Exercises

Chapter 10

• MNIST dataset MLP using Bayesian hyperparameter optimization
• Exercises

Chapter 11

• CIFAR 10 dataset deep MLP training
• Exercises

Chapter 12

• MNIST dataset custom Tensorflow training loop
• Custom layer normalization
• Exercises

Chapter 13

• MNIST dataset chunked TFRecord loading
• Large Movie Review dataset loading and preprocessing
• Exercises

Chapter 14

• MNIST dataset scratch CNN
• Labeled Faces in the Wild dataset transfer learning
• Neural Style Transfer tutorial
• Exercises

Chapter 15

• SketchRNN dataset using RNN classifier
• Bach Chorales dataset generative RNN
• Exercises

Chapter 16

• Reber Grammar dataset RNN classifier
• Date reformatting dataset Encoder-Decoder
• Neural Machine Translation tutorial
• Shakespeare dataset fine-tuning with Hugging Face Distil GPT2
• Ted Talk Portugese to English Neural Machine Translation with Transformer tutorial
• Exercises

Chapter 17

• CIFAR 10 dataset Denoising Autoencoder
• CIFAR 10 dataset Variational Autoencoder
• CIFAR 10 datset DCGAN
• Exercises