Python: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents using Python

by Giuseppe Bonaccorso, Armando Fandango, Rajalingappaa Shanmugamani

Get up to speed with machine learning techniques and create smart solutions for different problems Gaining expertise in artificial intelligence requires an in-depth understanding of the most popular machine learning algorithms. With this book, you'll be able to explore the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the most effective way possible. From Bayesian models, to the MCMC algorithm, and even Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll use TensorFlow and Keras to build deep learning models with concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll discover TensorFlow1.x's advanced features, such as distributed TensorFlow with TF clusters, and also understand the deployment of production models with TensorFlow Serving. As you progress, the book will guide you on how to implement techniques related to object classification, object detection, and image segmentation. By the end of this Python book, you'll have gained in-depth knowledge of TensorFlow, along with the skills you need for solving artificial intelligence problems. This Learning Path includes content from the following Packt This Learning Path is for data scientists, machine learning engineers, and artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve predictions of trained models. Basic knowledge of Python programming and machine learning concepts is required to get the most out of this book.

764 pages, Paperback

Published December 21, 2018

About the author

Experienced and goal-oriented senior executive leader with wide expertise in the management of Artificial Intelligence, Machine Learning, Deep Learning, and Data Science projects for healthcare, B2C and Military industries (Fortune 500 firms).

His main interests include Machine/Deep Learning, Reinforcement Learning, Advanced Analytics, Bio-inspired adaptive systems, Business Intelligence, Neuroscience, Neural Language Processing, Econometrics, Data Science Strategy and Organization.

Professional member of IEEE, IEEE Computer Society, AAAI, ACM, IAENG, AICA, SFIA, and Agile Manifesto.