Machine Learning in Python: Essential Techniques for Predictive Analysis
Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language.
- Predict outcomes using linear and ensemble algorithm families
- Build predictive models that solve a range of simple and complex problems
- Apply core machine learning algorithms using Python
- Use sample code directly to build custom solutions
Machine learning doesn’t have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Pythonshows you how to do this, without requiring an extensive background in math or statistics.
MICHAEL BOWLES teaches machine learning at Hacker Dojo in Silicon Valley, consults on machine learning projects, and is involved in a number of startups in such areas as bioinformatics and high-frequency trading. Following an assistant professorship at MIT, Michael went on to found and run two Silicon Valley startups, both of which went public. His courses at Hacker Dojo are nearly always sold out and receive great feedback from participants.