Getting Started with Artificial Intelligence , 2nd Edition

Tom Markiewicz, Josh Zheng

Comprehensive introduction to AI, covering machine learning and data science. Practical guide to building enterprise applications with real-world examples.

Technical TutorialsData ScienceMachine Learning

Introduction

Getting Started with Artificial Intelligence, 2nd Edition by Tom Markiewicz and Josh Zheng is a comprehensive introduction to artificial intelligence, covering topics such as machine learning and data science.

Highlights

  • Covers a wide range of AI topics, including machine learning and data science
  • Provides a practical guide to building enterprise applications with AI
  • Includes real-world examples and case studies

Recommendation

This course is recommended for anyone interested in learning about the practical applications of AI in the enterprise. It is suitable for both beginners and experienced professionals looking to integrate AI into their next project.

How GetVM Works

Learn by Doing from Your Browser Sidebar

Access from Browser Sidebar

Access from Browser Sidebar

Simply install the browser extension and click to launch GetVM directly from your sidebar.

Select Your Playground

Select Your Playground

Choose your OS, IDE, or app from our playground library and launch it instantly.

Learn and Practice Side-by-Side

Learn and Practice Side-by-Side

Practice within the VM while following tutorials or videos side-by-side. Save your work with Pro for easy continuity.

Explore Similar Hands-on Tutorials

Machine Learning For Dummies, IBM Limited Edition

19
Technical TutorialsData ScienceMachine Learning
Comprehensive guide to machine learning and data science, suitable for beginners and experienced professionals. Authored by experts Daniel Kirsch and Judith Hurwitz.

A Programmers Guide to Data Mining

14
Technical TutorialsData SciencePython
Comprehensive guide to data mining techniques, including recommendation systems, classification, and clustering. Beginner-friendly introduction for programmers with hands-on exercises and Python code.

Data Mining Concepts and Techniques

25
Technical TutorialsData ScienceMachine Learning
Comprehensive coverage of data mining concepts and techniques, including data preprocessing, classification, clustering, and association rule mining. Essential resource for students, researchers, and professionals in data mining, machine learning, and data analysis.

Foundations of Data Science

5
Technical TutorialsComputer ScienceData Science
Dive into the core principles and techniques of data science with this comprehensive course by renowned experts. Gain a strong foundation in algorithms, machine learning, and more.

Fundamentals of Data Visualization

4
Technical TutorialsData AnalysisData ScienceData Visualization
Comprehensive guide to understanding the principles and techniques of data visualization, covering design, perception, and communication of visual data. Practical insights and tools for creating effective visualizations.

Hands-On Data Visualization

9
Technical TutorialsData ScienceJavaScript
Comprehensive guide to data visualization techniques and best practices. Learn to design interactive charts and customized maps for your website using free and easy-to-learn tools.

High-Dimensional Data Analysis with Low-Dimensional Models: Principles, Computation, and Applications

10
Technical TutorialsComputer ScienceData ScienceMathematics
Comprehensive exploration of high-dimensional data analysis, covering real-world applications in medical imaging, computer vision, and more. Valuable resource for researchers and practitioners.

Mining of Massive Datasets

28
Technical TutorialsData Science
Comprehensive guide to data mining, machine learning, and analysis of massive datasets, including techniques for similarity search, data-stream processing, and graph analysis.

A Brief Introduction to Machine Learning for Engineers

29
Technical TutorialsMachine Learning
Gain a solid understanding of machine learning concepts and techniques for engineers. Covers supervised, unsupervised, probabilistic models, and advanced topics.