Today, I’m beginning a journey into Machine Learning, and I’ll write about it in this blog. In this post, I will discuss the materials I am using during my quest.

## Material

Here is the list of all the materials I used in my quest.

### Videos:

- Machine Learning Specialization by Andrew Ng
- Machine Learning with Python and Scikit-Learn – Full Course by freeCodeCamp
- Data Science Beginner Project: Kaggle House Prices Regression Analysis (Full Walkthrough) by Ryan Nolan

## My Journey

### Update May 30, 2024:

I’ll start my journey with the highly-rated Machine Learning Specialization course by Andrew Ng. This course consists of three parts:

- Course 1: Supervised Machine Learning: Regression and Classification – 33 hours
- Course 2: Advanced Learning Algorithms – 34 hours
- Course 3: Unsupervised Learning, Recommenders, Reinforcement Learning – 27 hours

### Update July 27, 2024:

I finished Course 1 of the Machine Learning Specialization. It was mostly theory, so I’ll watch other tutorials and practice with a test project to apply what I learned before starting the next course.

I spent some time finding a new course to complement the one I’m currently watching. Preferably, the course will include a project for practice. I found this free course on YouTube:

Machine Learning with Python and Scikit-Learn – Full Course

So far, I’ve watched the first lesson. It was good. The first lesson was a Linear Regression project, and to reinforce my learning, I’ll do another practice project before continuing to the next lesson.

### Update August 9, 2024:

I just finished this tutorial on YouTube: Data Science Beginner Project: Kaggle House Prices Regression Analysis (Full Walkthrough), and also submitted my first entry to a Kaggle competition.

Before proceeding with the course I mentioned in my previous update, I decided to undertake a practice project, and I found this tutorial to be very useful for practicing and learning.

Ready for lesson 2!