The manner in which computers are now able to mimic human thinking to process information is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest.
In the modern age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would.
But given it is a machine, it can consider many more scenarios and execute far more complicated calculations to solve complex problems.
This is the element that excites data scientists and machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning.
In this book we will dive in and consider machine learning from an aerial view to discern the relationship between our topic and the larger field of data science.
Table of Contents
- Overview of Data Science
- The Evolution of Data Science and the Information Age
- Big Data
- Machine Learning
- Data Mining
- Machine Learning Tools
- Machine Learning Case Studies
- Online Advertising
- Google’s Machine Learning
- Machine Learning Techniques
- Support Vector Machine Algorithms
- Artificial Neural Networks - Deep Learning
- Association Analysis
- Where to From Here
- Career Opportunities in Machine Learning
- Degrees & Certifications
- Final Word
- Title: Machine Learning for Absolute Beginners
- Author: Oliver Theobald
- Length: 69 pages
- Edition: 1
- Language: English
- Publication Date: 2017-02-18
- ISBN-10: B06VXKBLNG