Hands-On Unsupervised Learning with Python

Hands-On Unsupervised Learning with Python

Hands-On Unsupervised Learning with Python: Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more

Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python.

This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images.

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About the Book
Genres: Data Science, Machine Learning
Tags: Data Science, Machine Learning
ISBN: 9781789348279
About the Author
Giuseppe Bonaccorso

Giuseppe Bonaccorso is an experienced team leader/manager in AI, machine/deep learning solution design, management, and delivery. He got his MScEng in electronics in 2005 from the University of Catania, Italy, and continued his studies at the University of Rome Tor Vergata and the University of Essex, UK. His main interests include machine/deep learning, reinforcement learning, big data, bio-inspired adaptive systems, cryptocurrencies, and NLP.

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."