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
- Machine Learning with Python and Scikit-Learn – Full Course by freeCodeCamp
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!
Update December 22, 2024:
I finally finished this 18-hour tutorial on YouTube: Machine Learning with Python and Scikit-Learn – Full Course. It was a great course and such an interesting experience! I also shared a comment about my experience on the course video, so feel free to check it out there!
I learned a lot in this course! We went through different machine learning models and made a project as an exercise for each one using Kaggle competitions. Not only did I learn about machine learning models, but I also got a deeper understanding of how to explore, process, and prepare data before training a model, which is such an important step.
Overall, it covered the basics of supervised and unsupervised learning, data preprocessing, regression and classification models, clustering techniques like K-Means, dimensionality reduction with PCA, model evaluation, cross-validation, hyperparameter tuning, and more.
Heading for the next course soon…