Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

• Use scikit-learn to track an example ML project end to end

• Explore several models, including support vector machines, decision trees, random forests, and ensemble methods

• Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection

• Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers

• Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning