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Machine learning for dummies / by John Paul Mueller and Luca Massaron.
- Format:
- Book
- Author/Creator:
- Mueller, John, 1958- author.
- Massaron, Luca, author.
- Series:
- --For dummies.
- For dummies
- Language:
- English
- Subjects (All):
- Machine learning.
- Physical Description:
- 1 online resource (435 pages) : illustrations (some color).
- Other Title:
- --For dummies
- For dummies
- Place of Publication:
- Hoboken, New Jersey : John Wiley & Sons, Inc., 2016.
- Summary:
- Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data--or anything in between--this guide makes it easier to understand and implement machine learning seamlessly. Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning
- Notes:
- Includes index.
- Includes bibliographical references.
- Description based on print version record.
- ISBN:
- 1-119-24575-3
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