Take your first steps in the world of data science by understanding the tools and techniques of data analysisTrain efficient Machine Learning models in Python using the supervised and unsupervised learning methodsLearn how to use Apache Spark for processing Big Data efficientlyBook DescriptionJoin Frank Kane, who worked on Amazon and IMDb’s machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them.Based on Frank’s successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis.What you will learnLearn how to clean your data and ready it for analysisImplement the popular clustering and regression methods in PythonTrain efficient machine learning models using decision trees and random forestsVisualize the results of your analysis using Python’s Matplotlib libraryUse Apache Spark’s MLlib package to perform machine learning on large datasetsAbout the AuthorMy name is Frank Kane. I spent nine years at Amazon and IMDb, wrangling millions of customer ratings and customer transactions to produce things such as personalized recommendations for movies and products and "people who bought this also bought." I tell you, I wish we had Apache Spark back then, when I spent years trying to solve these problems there. I hold 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, I left to start my own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.Table of ContentsGetting StartedStatistics and Probability Refresher and Python PracticeMatplotlib and Advanced Probability ConceptsPredictive ModelsMachine Learning with PythonRecommender SystemsMore Data Mining and Machine Learning TechniquesDealing with Real-World DataApache Spark: Machine Learning on Big DataTesting and Experimental Design