Book Image

Step-by-Step Machine Learning with Python [Video]

By : Yuxi (Hayden) Liu
Book Image

Step-by-Step Machine Learning with Python [Video]

By: Yuxi (Hayden) Liu

Overview of this book

Data science and machine learning are some of the top buzzwords in the technical world today. The resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This video is your entry point to machine learning. It starts with an introduction to machine learning and the Python language and shows you how to complete the necessary setup. Moving ahead, you will learn all the important concepts such as exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression, and model performance evaluation. With the help of the various projects included, you will acquire the mechanics of several important machine learning algorithms, which will no longer seem obscure. Also, you will be guided step-by-step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and master best practices for applying machine learning techniques. Throughout this course, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple Python language. Interesting and easy-to-follow examples—including news topic classification, spam email detection, online ad click-through prediction, and stock prices forecasts—will keep you glued to the screen till you reach your goal.
Table of Contents (8 chapters)
Free Chapter
1
Getting Started with Python and Machine Learning
Chapter 4
News Topic Classification with Support Vector Machine
Content Locked
Section 5
Choosing Between the Linear and the RBF Kernel
This video will walk you through different scenarios where the linear kernel is favored over RBF. - Work with three scenarios where the linear kernel is preferred over RBF