Let's fabricate some experimental data and use the t-statistic and p-value to determine whether a given experimental result is a real effect or not. We're going to actually fabricate some fake experimental data and run t-statistics and p-values on them, and see how it works and how to compute it in Python.
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Book Overview & Buying
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Table Of Contents
Hands-On Data Science and Python Machine Learning
By :
Hands-On Data Science and Python Machine Learning
By:
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)
Free Chapter
Getting Started
Statistics and Probability Refresher, and Python Practice
Matplotlib and Advanced Probability Concepts
Predictive Models
Machine Learning with Python
Recommender Systems
More Data Mining and Machine Learning Techniques
Dealing with Real-World Data
Apache Spark - Machine Learning on Big Data
