Machine Learning 101 with Scikit-learn and StatsModels: Begin your machine learning journey by learning all about linear regression, logistic regression, and cluster analysis [Video]

Name: Machine Learning 101 with Scikit-learn and StatsModels [Video]
Brand: Packt
SKU: 9781838987671
Price: 183.99 USD
Availability: InStock

By 365 Careers Ltd.

$183.99

Video Jul 2019 5 hours 13 minutes 1st Edition

What do you get with a video?

Download this video in MP4 format

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Buy Now

View table of contents Download Code

Key benefits

Learn machine learning with StatsModels and sklearn
Apply machine learning skills to solve real-world business cases
Get started with linear regression, logistic regression, and cluster analysis

Description

Machine Learning is one of the fundamental skills you need to become a data scientist. It’s the steppingstone that will help you understand deep learning and modern data analysis techniques. In this course, you’ll explore the three fundamental machine learning topics - linear regression, logistic regression, and cluster analysis. Even neural networks geeks (like us) can’t help but admit that it’s these three simple methods that data science revolves around. So, in this course, we will make the otherwise complex subject matter easy to understand and apply in practice. This course supports statistics theory with practical application of these quantitative methods in Python to help you develop skills in the context of data science. We’ve developed this course with not one but two machine learning libraries: StatsModels and sklearn. You’ll be eager to complete this course and get ready to become a successful data scientist! All the code and supporting files for this course are available at https://github.com/PacktPublishing/Machine-Learning-101-with-Scikit-learn-and-StatsModels

What you will learn

Confidently work with two of the leading ML packages: statsmodels and sklearn Understand how to perform a linear regression Become familiar with the ins and outs of logistic regression Get to grips with carrying out cluster analysis (both flat and hierarchical) Apply your skills to real-life business cases Get insights into the underlying ideas behind ML models