Book Image

Hands-On Data Science and Python Machine Learning

By : Frank Kane
Book Image

Hands-On Data Science and Python Machine Learning

By: Frank Kane

Overview of this book

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.
Table of Contents (11 chapters)

A/B testing concepts

If you work as a data scientist at a web company, you'll probably be asked to spend some time analyzing the results of A/B tests. These are basically controlled experiments on a website to measure the impact of a given change. So, let's talk about what A/B tests are and how they work.

A/B tests

If you're going to be a data scientist at a big tech web company, this is something you're going to definitely be involved in, because people need to run experiments to try different things on a website and measure the results of it, and that's actually not as straightforward as most people think it is.

What is an A/B test? Well, it's a controlled experiment that you usually run on...