Artificial Intelligence and Machine Learning Fundamentals

Zsolt Nagy

ISBN 10: 1789801656 / ISBN 13: 9781789801651

Published by Packt Publishing Limited, GB, 2018

About this Item

Create AI applications in Python and lay the foundations for your career in data scienceKey FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail with interesting examplesMaster core AI concepts with engaging activitiesBook DescriptionMachine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples.As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law.By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!What you will learnUnderstand the importance, principles, and fields of AIImplement basic artificial intelligence concepts with PythonApply regression and classification concepts to real-world problemsPerform predictive analysis using decision trees and random forestsCarry out clustering using the k-means and mean shift algorithmsUnderstand the fundamentals of deep learning via practical examplesWho this book is forArtificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it's recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).

Seller Inventory # LU-9781789801651

Bibliographic Details

• Title: Artificial Intelligence and Machine Learning Fundamentals
• Publisher: Packt Publishing Limited, GB
• Publication Date: 2018
• Language: English
• ISBN 10: 1789801656
• ISBN 13: 9781789801651
• Binding: Paperback
• Condition: New

About this title

Synopsis

Create AI applications in Python and lay the foundations for your career in data science

Key Features

• Practical examples that explain key machine learning algorithms
• Explore neural networks in detail with interesting examples
• Master core AI concepts with engaging activities

Book Description

Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples.

As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law.

By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!

What you will learn

• Understand the importance, principles, and fields of AI
• Implement basic artificial intelligence concepts with Python
• Apply regression and classification concepts to real-world problems
• Perform predictive analysis using decision trees and random forests
• Carry out clustering using the k-means and mean shift algorithms
• Understand the fundamentals of deep learning via practical examples

Who this book is for

Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it's recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).

Table of Contents

1. Principles of Artificial Intelligence
2. AI with Search Techniques and Games
3. Regression
4. Classification
5. Using Trees for Predictive Analysis
6. Clustering
7. Deep Learning with Neural Networks

About the Author

Zsolt Nagy is an engineering manager in an ad tech company heavy on data science. After acquiring his MSc in inference on ontologies, he used AI mainly for analyzing online poker strategies to aid professional poker players in decision making. After the poker boom ended, he put extra effort into building a T-shaped profile in leadership and software engineering.