Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled...

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Ankur A. Patel

Hands-On Unsupervised Learning Using Python

How to Build Applied Machine Learning Solutions from Unlabeled Data

Ankur A. Patel

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English

O'Reilly Media
15 March 2019

Programming & scripting languages: general; Data capture & analysis; Neural networks & fuzzy systems; Pattern recognition; Computer vision

Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied. Unsupervised learning, on the other hand, can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover.

Author Ankur Patel shows you how to apply unsupervised learning using two simple, production-ready Python frameworks: Scikit-learn and TensorFlow using Keras. With code and hands-on examples, data scientists will identify difficult-to-find patterns in data and gain deeper business insight, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets. All you need is programming and some machine learning experience to get started.

Compare the strengths and weaknesses of the different machine learning approaches: supervised, unsupervised, and reinforcement learning

Set up and manage machine learning projects end-to-end

Build an anomaly detection system to catch credit card fraud

Clusters users into distinct and homogeneous groups

Perform semisupervised learning

Develop movie recommender systems using restricted Boltzmann machines

Generate synthetic images using generative adversarial networks

By: Ankur A. Patel
Imprint: O'Reilly Media
Country of Publication: United States
Dimensions: Height: 250mm, Width: 150mm, Spine: 15mm
Weight: 666g
ISBN: 9781492035640
ISBN 10: 1492035645
Pages: 400
Publication Date: 15 March 2019
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Ankur Patel is an applied machine learning researcher and data scientist with expertise in financial markets. His work focuses on unsupervised learning, natural language processing, time series prediction, and sequential data problems. Currently, Ankur finds hidden patterns in large-scale unlabeled data for clients around the world as a data scientist at ThetaRay, an Israeli artificial intelligence firm. Ankur started his career as the lead emerging markets trader at Bridgewater Associates and later founded and managed the machine learning-based hedge fund R-Squared Macro.