Understanding Machine Learning with Python

Use your data to predict future events with the help of machine learning. This course will walk you through creating a machine learning prediction solution and will introduce Python, the scikit-learn library, and the Jupyter Notebook environment.
Course info
Rating
(505)
Level
Beginner
Updated
May 17, 2016
Duration
1h 54m
Table of contents
Description
Course info
Rating
(505)
Level
Beginner
Updated
May 17, 2016
Duration
1h 54m
Description

Hello! My name is Jerry Kurata, and welcome to Understanding Machine Learning with Python. In this course, you will gain an understanding of how to perform Machine Learning with Python. You will get there by covering major topics like how to format your problem to be solvable, how to prepare your data for use in a prediction, and how to combine that data with algorithms to create models that can predict the future. By the end of this course, you will be able to use Python and the scikit-learn library to create Machine Learning solutions. And you will understand how to evaluate and improve the performance of the solutions you create. Before you begin, make sure you are already familiar with software development and basic statistics. However, your software experience does not have to be in Python, since you will learn the basics in this course. When you use Python together with scikit-learn, you will see why this is the preferred development environment for many Machine Learning practitioners. You will do all the demos using the Jupyter Notebook environment. This environment combines live code with narrative text to create a document with can be executed and presented as a web page. I hope you’ll join me, and I look forward to helping you on your learning journey here at Pluralsight.

About the author
About the author

Jerry Kurata is a Solutions Architect at InStep Technologies.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi, my name is Jerry Kurata, and welcome to my course, Understanding Machine Learning with Python. These days, machine learning is all around us, from helping doctors diagnose patients to assisting us in driving our cars. As we go about our day, we may be utilizing machine learning applications and not even realize it. It silently scans our email inboxes for spam emails and ensures that stores are stocked with the goods we want to buy when we need them. This course will introduce you to machine learning and the technology behind it. You will see why companies are in such a rush to use machine learning to grow their business and increase profits. You will learn how developers and data scientists use machine learning to predict events based on data, specifically you will learn how to format a problem to be solvable, where to get the data, and how to combine that data with algorithms to create models that can predict the future. Throughout this course, we'll utilize Python and a number of its libraries to make creating machine learning solutions easy. However, you do not need prior experience with Python. In this course, we learn by doing, and the code we will use will be explained as we create our solution. By the end of this course, you will know the how, when, and why of building a machine learning solution with Python. You will have the skills you need to transform a one-line problem statement into a tested prediction model that solves the problem. I look forward to you joining me on this journey of understanding machine learning with Python from Pluralsight.