Hands-On Data Science and Python Machine Learning

Anglický jazyk

Hands-On Data Science and Python Machine Learning

Na objednávku, dodanie 2-4 týždne

47.25 €

bežná cena: 52.50 €

O knihe

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.

Key Features

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

Book Description

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.

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