Machine Learning : A Beginner's Basic Introduction

Machine Learning : A Beginner's Basic Introduction, available at $34.99, has an average rating of 4.05, with 17 lectures, based on 350 reviews, and has 25414 subscribers.

You will learn about 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 This course is ideal for individuals who are Absolute beginners to Machine Learning It is particularly useful for Absolute beginners to Machine Learning.

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Summary

Title: Machine Learning : A Beginner's Basic Introduction

Price: $34.99

Average Rating: 4.05

Number of Lectures: 17

Number of Published Lectures: 17

Number of Curriculum Items: 17

Number of Published Curriculum Objects: 17

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

Absolute beginners to Machine Learning

Target Audiences

Absolute beginners to Machine Learning

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.

Course Curriculum

Chapter 1: Setting up test environment

Lecture 1: Introduction

Lecture 2: What is Python

Lecture 3: Installing Python

Lecture 4: Installing Pycharm

Lecture 5: Installing Anaconda

Chapter 2: Machine Learning Basics

Lecture 1: What is Machine Learning

Lecture 2: Machine Learning Frameworks

Lecture 3: Machine Learning Vocabulary

Lecture 4: Supervised Machine Learrning

Lecture 5: Where Machine Learning is Used

Lecture 6: Creating a basic house value estimator

Lecture 7: Using scikit-learn

Lecture 8: Loading a Dataset Part 1

Lecture 9: Loading a Dataset Part 2

Lecture 10: Making predictions – Part 1

Lecture 11: Making predictions – Part 2

Lecture 12: Thank You

Instructors

Bluelime Learning Solutions
Making Learning Simple

Rating Distribution

1 stars: 12 votes
2 stars: 28 votes
3 stars: 81 votes
4 stars: 102 votes
5 stars: 127 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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