Python: Machine Learning with Python

$99.00 $49.99

This Machine Learning with Python course begins with an introduction to machine learning concepts, after which you’ll build your first machine learning application. Following that, we look at data analysis, linear algebra, natural language processing and clustering, all within the context of Python.

Length: 5 hrs

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Description

This Machine Learning with Python course will show you what’s what, and get you started on becoming a machine learning guru.

If you’re plugged into the tech industry, you’ll know that two things have been making consistent waves in many areas over the past few years; machine learning and Python. What happens when you combine the new gold standard programming language with the most significant tech development in areas such as financial trading, online search, digital marketing and even data and personal security (among others)? Great things, that’s what.

Learn the New Future of Programming!

  • Understand what machine learning is and what it can do
  • Discover how Python utilizes machine learning
  • Build machine learning processing from the ground up
  • Delve into complex logic and data structures
  • Increase Your Python Expertise

Linear Algebra, Natural Language and more!  If you have a desire to learn machine learning concepts and have some previous programming or Python experience, this course is perfect for you. If you’re more of a beginner than an intermediate, don’t worry; each module starts with theory to explain upcoming concepts. Once you’re comfortable, you’ll put your knowledge into practice with a code walk through.

The goal of this course is to build procedural machine learning from the ground up. Writing processing from scratch allows students to gain a more in-depth insight into data processing, and as each machine learning app is created, explanations and comments are provided to help students understand why things are being done in certain ways. Each code walk through also shows the building process in real time.

What is Machine Learning?

Machine learning is a method of data analysis that essentially allows computers to ‘learn’ on their own without being explicitly programmed. For example, when you stop scrolling through Facebook to read a friend or a page’s post, algorithms automatically work to make sure you’ll see more content from those sources earlier in your news feed in future.

Sample clip

 

CHAPTER 1: COURSE INTRODUCTION
Course Introduction
 
CHAPTER 2: MACHINE LEARNING CONCEPTS
Section Introduction
Supervised and Unsupervised Learning
Semi-Supervised Learning
Section Summary
 
CHAPTER 3: FIRST ML APPLICATION
Section Introduction
Installing the Environment
Hello World
Installing Aaconda and Deep Learning Libraries
Email Spam Checker – Part 1
Email Spam Checker – Part 2
Email Spam Checker Results
Iris 70:30 – Part 1
Iris 70:30 – Part 2
Section Summary
 
CHAPTER 4: DATA ANALYSIS
Section Introduction
Data Analysis – Example 1
Data Analysis – Example 2
Data Visualization
Section Summary
 
CHAPTER 5: LINEAR ALGEBRA
Section Introduction
Parametric Algorithms
Linear Algebra
Linear Regression Calculation – Part 1
Linear Regression Calculation – Part 2
Regression on Larger Dataset – Part 1
Regression on Larger Dataset – Part 2
Regression on Larger Dataset – Part 3
Section Summary
 
CHAPTER 6: NATURAL LANGUAGE PROCESSING
Section Introduction
Natural Language Processing – Part 1
Natural Language Processing – Part 2
Tokenizing Content
Processing Unique Words
Summarizing Headlines – Part 1
Summarizing Headlines – Part 2
Summarizing Headlines – Part 3
Section Summary
 
CHAPTER 7: CLUSTERING
Section Introduction
Cluster Introduction
EM and M Clustering
Clustering Code Walkthrough
Clustering Iris Data – Part 1
Clustering Iris Data – Part 2
Clustering Iris Data – Part 3
Dendrogram Graphs
Section Summary
Course Summary

Brett Romero is a software engineer and entrepreneur. He has started several businesses, including Bitesize Business School, where he writes about applying business principles to the real world and solving technology issues that every online business faces. His first business, Cygen, was a web design consulting business, from which he also created his first product – a JavaScript-based chatroom web application.

Brett has written desktop applications in languages running from Delphi to C# winforms/WPF, as well as built ASP.NET webforms and MVC based applications. When the iOS SDK was first introduced, he bought a Macbook and began building apps for the iPhone. He currently has seven apps in the iTunes App Store.

Brett holds an MBA from ASU (’14). His undergraduate major was in mathematics. Before graduating, he decided to get a business degree. He continued taking mathematics courses at the University of Washington after completing his undergraduate degree.

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