Machine Learning : A Beginner's Basic Introduction
4.0 (99 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
2,583 students enrolled

Machine Learning : A Beginner's Basic Introduction

Learn Machine Learning Basics with a Practical Example
4.0 (99 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
2,583 students enrolled
Last updated 3/2018
English
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Current price: $62.99 Original price: $104.99 Discount: 40% off
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This course includes
  • 2 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Install environment to test Machine learning
  • Understand basic machine learning vocabulary
  • Exposure to Machine Learning Frameworks
  • Understand Supervised Machine Learning
  • Create a basic home estimator calculator
  • Load a Dataset
  • Make Predictions from dataset
Course content
Expand all 16 lectures 01:47:25
+ Machine Learning Basics
11 lectures 01:19:29
What is Machine Learning
10:13
Machine Learning Frameworks
06:16
Machine Learning Vocabulary
06:32
Supervised Machine Learrning
08:31
Where Machine Learning is Used
04:54
Creating a basic house value estimator
11:17
Using scikit-learn
08:41
Loading a Dataset Part 1
08:29
Loading a Dataset Part 2
03:05
Making predictions - Part 1
07:46
Making predictions - Part 2
03:45
Requirements
  • You should be able to use a PC at beginner level
  • Basic knowledge of Python would help but not mandatory
Description

Machine learning relates to many different ideas, programming languages, frameworks. Machine learning is difficult to define in just a sentence or two. But essentially, machine learning is giving a computer the ability to write its own rules or algorithms and learn about new things, on its own. In this course, we'll explore some basic machine learning concepts and load data to make predictions.

Value estimation—one of the most common types of machine learning algorithms—can automatically estimate values by looking at related information. For example, a website can determine how much a house is worth based on the property's location and characteristics.
In this course, we will  use machine learning to build a value estimation system that can deduce the value of a home.   Although the tool  we will build in this course focuses on real estate, you can use the same approach to solve any kind of value estimation.

What you'll learn include:
  • Basic concepts in machine learning
  • Supervised versus Unsupervised learning
  • Machine learning frameworks
  • Machine learning using Python and scikit-learn
  • Loading sample dataset
  • Making predictions based on dataset
  • Setting up the development environment
  • Building a simple home value estimator

The examples in this course are basic but should give you a solid understanding of the power of machine learning and how it works.

Who this course is for:
  • Absolute beginners to Machine Learning