Download Hands-On Unsupervised Learning Using Python: PDF Free ePUB

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

Overview

Review

Comments

Download PDF

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 using Keras. With the hands on examples and code provided, you 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 learningSet up and manage a machine learning project end to end everything from data acquisition to building a model and implementing a solution in productionUse dimensionality reduction algorithms to uncover the most relevant information in data and build an anomaly detection system to catch credit card fraudApply clustering algorithms to segment users such as loan borrowers into distinct and homogeneous groupsUse autoencoders to perform automatic feature engineering and selectionCombine supervised and unsupervised learning algorithms to develop semi supervised solutionsBuild movie recommender systems using restricted Boltzmann machinesGenerate synthetic images using deep belief networks and generative adversarial networksPerform clustering on time series data such as electrocardiogramsExplore the successes of unsupervised learning to date and its promising future

Details e-book Hands-On Unsupervised Learning Using Python

🗸 Author(s): Ankur A. Patel
🗸 Title: Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data
🗸 Rating : 4.1 from 5 stars (80 reviews)
🗸 Languange: English
🗸 Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
🗸 Supported Devices: Android, iOS, PC and Amazon Kindle

Readers' opinions about Hands-On Unsupervised Learning Using Python by Ankur A. Patel

Jenene Andrews
This gripping thriller takes readers on a rollercoaster ride through the dark alleys of a crime-ridden city, where the protagonists must unravel a complex web of deceit to solve a murder. The plot twists are relentless, keeping readers on the edge of their seats until the final revelation. With its well-developed characters and gritty atmosphere, this book is a must-read for fans of the genre.

Sherle Mitchell
Explore the mysteries of the universe with this fascinating exploration of astronomy and cosmology. From the origins of the universe to the search for extraterrestrial life, the author takes readers on a journey through the cosmos, shedding light on some of the universe's most profound mysteries. With its accessible language and engaging narrative, this book is a perfect introduction to the wonders of the cosmos.

Miya Yates
This captivating science fiction novel transports readers to a distant future where humanity has colonized the stars and forged new alliances among the cosmos. Against the backdrop of interstellar conflict, the story follows a group of intrepid explorers as they journey to the far reaches of space in search of a lost civilization. With its gripping plot twists and richly imagined world-building, this book is a thrilling adventure that will leave readers eagerly anticipating the next installment.