Availability: In Stock

Artificial Intelligence and Machine Learning Fundamentals (1 ed)

Author: Zsolt Nagy
SKU: BF-0266

Original price was: $32.82.Current price is: $5.00.

  • Publisher: Packt
  • Author: Zsolt Nagy
  • Language: ‎English
  • Format: ‎PDF
  • Pages: 330 pages

Description

Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances 1st Edition

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 begin 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.

After reading this book, you'll be ready to build AI apps with your new 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 are 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 know 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

Additional information

Author

Publisher

Packt

Format

PDF

Language

English

Reviews

There are no reviews yet.

Be the first to review “Artificial Intelligence and Machine Learning Fundamentals (1 ed)”

Your email address will not be published. Required fields are marked *