Machine Learning 101 with Scikit-learn and StatsModels / Careers, 365.

Format:

Video

Author/Creator:

Careers, 365, author.

Language:

English

Subjects (All):

Machine learning.

Neural networks (Computer science).

Regression analysis.

Statistics--Data processing.

Statistics.

Genre:

Electronic videos.

Physical Description:

1 online resource (1 video file, approximately 5 hr., 13 min.)

Edition:

1st edition

Other Title:

Machine learning one hundred and one with Scikit-Learn and StatsModels

Place of Publication:

Packt Publishing, 2019.

System Details:

video file

Summary:

New to machine learning? This is the place to start: Linear regression, Logistic regression, and Cluster Analysis About This Video 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 In Detail 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!

Notes:

Online resource; Title from title screen (viewed July 10, 2019)

Title from resource description page (Safari, viewed February 18, 2020).

OCLC:

1141018051