This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark.

About This Book

• Take your first steps in the world of data science by understanding the tools and techniques of data analysis
• Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods
• Learn how to use Apache Spark for processing Big Data efficiently

Who This Book Is For

If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book.

What You Will Learn

• Learn how to clean your data and ready it for analysis
• Implement the popular clustering and regression methods in Python
• Train efficient machine learning models using decision trees and random forests
• Visualize the results of your analysis using Python's Matplotlib library
• Use Apache Spark's MLlib package to perform machine learning on large datasets

In Detail

Join 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.

Style and approach

This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.

Osoby które kupowały "Hands-On Data Science and Python Machine Learning", wybierały także:

• Oracle Database 12c. Programowanie w jÄ™zyku PL/SQL 146,34 zÅ‚, (81,95 zÅ‚ -44%)
• Bazy danych. Podstawy projektowania i jÄ™zyka SQL 34,89 zÅ‚, (26,17 zÅ‚ -25%)
• Head First PHP & MySQL. Edycja polska 99,00 zÅ‚, (74,25 zÅ‚ -25%)
• MySQL. Mechanizmy wewnÄ™trzne bazy danych 37,00 zÅ‚, (27,75 zÅ‚ -25%)
• Metody i techniki odkrywania wiedzy. NarzÄ™dzia CAQDAS w procesie analizy danych jakoÅ›ciowych 28,99 zÅ‚, (22,90 zÅ‚ -21%)

Spis treści

Hands-On Data Science and Python Machine Learning. Perform data mining and machine learning efficiently using Python and Spark eBook -- spis treści

• 1. Getting Started
• 2. Statistics and Probability Refresher and Python Practice
• 3. Matplotlib and Advanced Probability Concepts
• 4. Predictive Models
• 5. Machine Learning with Python
• 6. Recommender Systems
• 7. More Data Mining and Machine Learning Techniques
• 8. Dealing with Real-World Data
• 9. Apache Spark: Machine Learning on Big Data
• 10. Testing and Experimental Design