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Artificial Intelligence with Python
Artificial Intelligence with Python

Artificial Intelligence with Python: Your complete guide to building intelligent apps using Python 3.x , Second Edition

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Profile Icon Alberto Artasanchez Profile Icon Joshi
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$38.99 $43.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.9 (20 Ratings)
eBook Jan 2020 618 pages 2nd Edition
eBook
$38.99 $43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Alberto Artasanchez Profile Icon Joshi
Arrow right icon
$38.99 $43.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.9 (20 Ratings)
eBook Jan 2020 618 pages 2nd Edition
eBook
$38.99 $43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$38.99 $43.99
Paperback
$54.99
Subscription
Free Trial
Renews at $19.99p/m

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Artificial Intelligence with Python

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Key benefits

  • Completely updated and revised to Python 3.x
  • New chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineering
  • Learn more about deep learning algorithms, machine learning data pipelines, and chatbots

Description

Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques.

Who is this book for?

The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.

What you will learn

  • Understand what artificial intelligence, machine learning, and data science are
  • Explore the most common artificial intelligence use cases
  • Learn how to build a machine learning pipeline
  • Assimilate the basics of feature selection and feature engineering
  • Identify the differences between supervised and unsupervised learning
  • Discover the most recent advances and tools offered for AI development in the cloud
  • Develop automatic speech recognition systems and chatbots
  • Apply AI algorithms to time series data

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jan 31, 2020
Length: 618 pages
Edition : 2nd
Language : English
ISBN-13 : 9781839216077
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Product Details

Publication date : Jan 31, 2020
Length: 618 pages
Edition : 2nd
Language : English
ISBN-13 : 9781839216077
Category :
Languages :
Tools :

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Table of Contents

25 Chapters
Introduction to Artificial Intelligence Chevron down icon Chevron up icon
Fundamental Use Cases for Artificial Intelligence Chevron down icon Chevron up icon
Machine Learning Pipelines Chevron down icon Chevron up icon
Feature Selection and Feature Engineering Chevron down icon Chevron up icon
Classification and Regression Using Supervised Learning Chevron down icon Chevron up icon
Predictive Analytics with Ensemble Learning Chevron down icon Chevron up icon
Detecting Patterns with Unsupervised Learning Chevron down icon Chevron up icon
Building Recommender Systems Chevron down icon Chevron up icon
Logic Programming Chevron down icon Chevron up icon
Heuristic Search Techniques Chevron down icon Chevron up icon
Genetic Algorithms and Genetic Programming Chevron down icon Chevron up icon
Artificial Intelligence on the Cloud Chevron down icon Chevron up icon
Building Games with Artificial Intelligence Chevron down icon Chevron up icon
Building a Speech Recognizer Chevron down icon Chevron up icon
Natural Language Processing Chevron down icon Chevron up icon
Chatbots Chevron down icon Chevron up icon
Sequential Data and Time Series Analysis Chevron down icon Chevron up icon
Image Recognition Chevron down icon Chevron up icon
Neural Networks Chevron down icon Chevron up icon
Deep Learning with Convolutional Neural Networks Chevron down icon Chevron up icon
Recurrent Neural Networks and Other Deep Learning Models Chevron down icon Chevron up icon
Creating Intelligent Agents with Reinforcement Learning Chevron down icon Chevron up icon
Artificial Intelligence and Big Data Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.9
(20 Ratings)
5 star 45%
4 star 25%
3 star 10%
2 star 10%
1 star 10%
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John G Feb 20, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I love the format. Each chapter starts with telling you what you'll learn in that chapter, then teaches, then recaps what you learned in the chapter. It also has an easy, approachable style that covers highly technical topics in real-world terms.If you're working in AI, want to work in AI, or want to know more about AI, this is a great book to read!
Amazon Verified review Amazon
Pragmatic AI Labs Feb 23, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
After reading through a review copy I was impressed by the cookbook style approach. Often the best purpose of a book is to provide a guide for people interested in getting started with a particular approach. This book serves that purpose and is a great complement to any ML or AI programmer's toolkit.
Amazon Verified review Amazon
Trebor May 11, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
There are many books out there on machine learning with Python, however not many have a well thought out process that walks you along both conceptual and development practices with ease as this book. A great book for someone new to even someone with experience who wants to extend their technical acumen beyond the theory.
Amazon Verified review Amazon
Frank Rotonta Mar 31, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book provides a great overview. It is for all skill levels.The book is well balanced between theory and application and does a thorough review of best practices and concepts.It is a well written and well thought out book and I enjoyed it.
Amazon Verified review Amazon
sipy Mar 27, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I don't recall ever giving any book 5 stars before. This book deserves it! So full of short snippets of fact and code. Doesn't waste time, just gets you working. The title suffers from the same marketing hype all books in this field does - the incorrect use of "Artificial Intelligence", when it really means "Machine Learning". Doesn't matter (there is no, true AI yet...). Good study on building feature engineering pipelines.
Amazon Verified review Amazon
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