How to use Scikit-Learn to buid a supervised learning model
Instructed by: Mike West | Subject: IT & Software, Operating Systems
Instructed by: Mike West | Subject: IT & Software, Operating Systems
Description
Python is one of the most popular languages for machine learning and in the course we’ll gently introduce you to SciKit-Learn, a library designed for working with machine learning projects. Scikit-Learn, also known as sklearn, is Python's premier general-purpose machine learning library. Scikit-Learn's versatility makes it the best starting place for most ML problems. Scikit-Learn is great for beginners it offers a high-level interface for many tasks. This allows you to better practice the entire machine learning workflow and understand the big picture. We will also gently introduce you to the vernacular of machine learning. For example, a target variable is simply that thing we are trying to predict. A feature is often no more than a column in at table.Outcome
- At the end of the course you'll understand how to create an end to end model using Python's SciKit_Learn.
- You'll understand the nomenclature and process when creating a solution in SciKit_Learn.
- You will also have a Jupyter Notebook that's annotated with all the important points in the course.
- You will also receive a completed Jupyter Notebook filled with models and references.
Course Info
- 17 Lectures
- 1 Hour
- Language: English
- Subject: IT & Software, Operating Systems
- Instructed by: Mike West
- Last updated on April 2017
- Platform: Udemy
