O'Reilly logo

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Machine Learning with Python

Video Description

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. This course will show you what’s what, and get you started on becoming a machine learning guru. Learn the New Future of Programming • Understand what machine learning is and what it can do • Discover how Python utilises machine learning • Build machine learning processing from the ground up • Delve into complex logic and data structures

Table of Contents

  1. Course Introduction 00:02:02
  2. Machine Learning Concepts
    1. Section 1 Introduction 00:00:39
    2. Supervised and Unsupervised Learning 00:08:34
    3. Semi-Supervised Learning 00:04:25
    4. Section 1 Summary 00:00:23
  3. First ML Application
    1. Section 2 Introduction 00:01:50
    2. Installing the Environment 00:02:54
    3. Hello World 00:07:34
    4. Installing Aaconda and Deep Learning Libraries 00:10:18
    5. Email Spam Checker - Part 1 00:07:09
    6. Email Spam Checker - Part 2 00:13:39
    7. Email Spam Checker Results 00:08:35
    8. Iris 70/30 - Part 1 00:08:56
    9. Iris 70/30 - Part 2 00:09:18
    10. Section 2 Summary 00:00:45
  4. Data Analysis
    1. Section 3 Introduction 00:00:32
    2. Data Analysis - Example 1 00:12:57
    3. Data Analysis - Example 2 00:10:47
    4. Data Visualization 00:08:44
    5. Section 3 Summary 00:00:45
  5. Linear Algebra
    1. Section 4 Introduction 00:01:00
    2. Parametric Algorithms 00:06:53
    3. Linear Algebra 00:09:36
    4. Linear Regression Calculation - Part 1 00:12:42
    5. Linear Regression Calculation - Part 2 00:05:04
    6. Regression on Larger Dataset - Part 1 00:10:18
    7. Regression on Larger Dataset - Part 2 00:07:38
    8. Regression on Larger Dataset - Part 3 00:10:09
    9. Section 4 Summary 00:00:39
  6. Natural Language Processing
    1. Section 5 Introduction 00:01:03
    2. Natural Language Processing - Part 1 00:08:57
    3. Natural Language Processing - Part 2 00:03:58
    4. Tokenizing Content 00:11:21
    5. Processing Unique Words 00:13:12
    6. Summarizing Headlines - Part 1 00:09:19
    7. Summarizing Headlines - Part 2 00:11:55
    8. Summarizing Headlines - Part 3 00:08:32
    9. Section 5 Summary 00:00:50
  7. Clustering
    1. Section 6 Introduction 00:01:03
    2. Cluster Introduction 00:08:31
    3. EM and M Clustering 00:06:19
    4. Clustering Code Walkthrough 00:09:07
    5. Clustering Iris Data - Part 1 00:08:57
    6. Clustering Iris Data - Part 2 00:08:44
    7. Clustering Iris Data - Part 3 00:08:16
    8. Dendrogram Graphs 00:10:02
    9. Section 6 Summary 00:01:00
    10. Course Summary 00:02:00