Python: Advanced Guide to Artificial Intelligence

Python: Advanced Guide to Artificial Intelligence

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

This Learning Path 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. Ranging from Bayesian models to the MCMC algorithm to 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 bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more.

By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems

This Learning Path includes content from the following Packt products:

  • Mastering Machine Learning Algorithms by Giuseppe Bonaccorso
  • Mastering TensorFlow 1.x by Armando Fandango
  • Deep Learning for Computer Vision by Rajalingappaa Shanmugamani

What you will learn

  • Explore how an ML model can be trained, optimized, and evaluated
  • Work with Autoencoders and Generative Adversarial Networks
  • Explore the most important Reinforcement Learning techniques
  • Build end-to-end deep learning (CNN, RNN, and Autoencoders) models

Who this book is for

This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model.

You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.

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About the Book
Series: Machine Learning Algorithms
Genres: Data Science, Machine Learning
Tags: Data Science, Deep Learning, Machine Learning
ISBN: 9781789957211
Disclosure of Material Connection: Some of the links in the page above are "affiliate links." This means if you click on the link and purchase the item, I will receive an affiliate commission. I am disclosing this in accordance with the Federal Trade Commission's 16 CFR, Part 255: "Guides Concerning the Use of Endorsements and Testimonials in Advertising."