Machine Learning 101 – Introduction to Machine Learning Course

This is the very first of a complete Machine Learning course .

So if you intend to learn Machine Learning, then you are in the right place. We would start from the absolute basics. Then we would move on to cover advanced topics.



The course assumes you belong to one of the categories below

  • You have a science background.
  • Or probably you are passionate about Artificial Intelligence.
  • Or maybe, you are an enthusiast and want to do what it takes to learn machine learning
  • You may also be a programmer
  • You have a finance/accounting/economics background
  • You would like to apply machine learning or financial modelling
  • Someone that loves challenges
  • Someone that loves math

So if any of the above describes you, then tighten your seat belts.


How This Tutorial is Arranged

Weekly Lesson: Every  week or twice a week, there would be a lesson. Accompanied by each lesson would be a corresponding video lesson

Practical Session: After each period (say two weeks), we would have a practical session using any of the tools we would outline

Interaction: It is expected that everyone follows carefully. If you miss something not clear, mention it in a comment under the lesson. So you can receive needed support before the next lesson

Quiz and Homework: Periodically, you will receive a quiz or a homework. Ensure to do it promptly.


Applications You Need

Python and Jupyter Notebook: To get these application, please download and install Anaconda. Anaconda is a distribution of Python the bundles with Jupyter Notebook.  It is free. Just in case you don’t know, Jupyter notebook is an application for writing machine learning models in Python. Download Anaconda from here.

R-Studio(Optional): I would recommend you download and install RStudio. You can get the free version. It’s an alternative to Python and Jupyter Notebook, though Python is more feature-rich. But since R-Studio is light-weight, I would recommend having it in your system. Some tasks performed in R-Studio makes it clearer. Download RStudio from here.

ML.NET (for .Net programmers): If you are a .Net programmer, then you need know how to add ML.Net to your Visual Studio solution using Nugget Package Manager. We would go through this later anyway.

MatLAB (Optional): If you would like to get to the core of every lesson, then also have MatLAB. Or maybe, you want to go further with Data Science.


Some Machine Learning Nuggets

There have been some lessons I have made in Machine Learning. I recommend you read them up at your leisure time. However, we would gradually cover every bit of any previous lessons I have made.



Learn difference between Artificial Intelligence, Machine Learning and Deep Learning

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Kindson Munonye is currently completing his doctoral program in Software Engineering in Budapest University of Technology and Economics

View all posts by kindsonthegenius →

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