Learn all the prerequisites to get into learning the concepts of machine learning
Hello Machine Learning Enthusiasts!
What you’ll learn
- Basics of Python programming useful for machine learning.
- Basics of Statistics useful for machine learning.
- To import module and important packages for machine learning.
- About the data set, which is important to implement machine learning.
Course Content
- Introduction –> 4 lectures • 10min.
- Python for Machine Learning –> 4 lectures • 47min.
- Packages and Statistics for Machine Learning –> 7 lectures • 1hr 4min.
Requirements
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
- 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.