Prerequisites to Machine Learning: A Beginners Guide
Learn all the prerequisites to get into learning the concepts of machine learning
Machine Learning,Data Science,Development
Lectures -15
Resources -13
Duration -2 hours
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Course Description
Hello Machine Learning Enthusiasts!
Are you making the same mistakes that 99% of fresh machine learning students do?
Yes…
Order is important to learn anything. And if you guessed correctly, you realize how important it is to understand certain things before moving on to others.
So, if you are interested to learn Machine Learning, but no idea where to start from, then this course is exactly for you.
This course “Prerequisites to Machine Learning: A Beginners Guide” has been designed in such a way that you will get clear path to move into learning the concepts and implementations of machine learning.
This course is entertaining and interesting, and it covers all the prerequisites to learn Machine Learning. It is organized in the following manner:
Section-1: Introduction
Course Overview
Meet Your Instructor
Introduction to Machine Learning
Google Colab Notebook
Section-2: Python for Machine Learning
Print Statement and Variables
Functions
Range, Lists, Tuples
Importing Modules
Section-3: Packages and Statistics for Machine Learning (Basics for Machine Learning)
NumPy
Pandas
Matplotlib
Mean, Median and Mode
Variance and Standard Deviation
Furthermore, the curriculum is dip with practical exercises. As a result, you'll not only discover the theory, but you'll also get some practice.
This course also provides the downloadable resources Python Code, executed on Google Colab Notebook, and Data Set that you can practice or use on your own projects as a bonus.
Goals
Basics of Python programming useful for machine learning
Basics of Statistics useful for machine learning
Importing module and packages for machine learning
About the data set, which is important to implement machine learning
Prerequisites
Need only basics of computer.
Need only high school mathematics.
- No programming experience needed.
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Curriculum
Check out the detailed breakdown of what’s inside the course
Section-1: Introduction
4 Lectures
-
Course Overview 01:36 01:36
-
Meet Your Instructor
-
Introduction to Machine Learning 03:20 03:20
-
Google Colab Notebook 04:13 04:13
Section-2: Python for Machine Learning
4 Lectures
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Section-3: Packages and Statistics for Machine Learning
7 Lectures
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Instructor Details
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Dr. Hesam Akhtar
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