Python: Advanced Guide to Artificial Intelligence

Python: Advanced Guide to Artificial Intelligence is your complete guide to quickly getting to grips with popular machine learning algorithms. You’ll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. (Limited-time offer)

Table of Contents

• Machine Learning Model Fundamentals
• Introduction to Semi-Supervised Learning
• Graph-Based Semi-Supervised Learning
• Bayesian Networks and Hidden Markov Models
• EM Algorithm and Applications
• Hebbian Learning and Self-Organizing Maps
• Clustering Algorithms
• Advanced Neural Models
• Classical Machine Learning with TensorFlow
• Neural Networks and MLP with TensorFlow and Keras
• RNN with TensorFlow and Keras
• CNN with TensorFlow and Keras
• Autoencoder with TensorFlow and Keras
• TensorFlow Models in Production with TF Serving
• Deep Reinforcement Learning
• Generative Adversarial Networks
• Distributed Models with TensorFlow Clusters
• Debugging TensorFlow Models
• Tensor Processing Units
• Getting Started
• Image Classification
• Image Retrieval
• Object Detection
• Semantic Segmentation
• Similarity Learning

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