Hands-on Unsupervised Learning (free) Download Full | **UPDATE

Hands-on Unsupervised Learning Free Download

Hands-on Unsupervised Learning (free) Download Full | **UPDATE. Unsupervised learning is a machine learning technique that allows computers to learn from data without being explicitly programmed. This is in contrast to supervised learning, which requires labeled data to train the model. Unsupervised learning is often used for exploratory data analysis, clustering, and dimensionality reduction.

This book provides a comprehensive overview of unsupervised learning, with a focus on practical applications. It covers a wide range of topics, including: * Different types of unsupervised learning algorithms * How to choose the right algorithm for your data * How to implement unsupervised learning algorithms in Python * How to evaluate the performance of unsupervised learning models

Hands-on Unsupervised Learning: This repo contains the code for the O'Reilly Media, Inc. book "Hands-on Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" by Ankur A. Patel. Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. Unsupervised learning 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 provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data.