Machine Learning has received a lot of attention, and rightly so. It has revolutionized several industries it has been introduced in.
I want to try to understand the technology behind Machine Learning for several reasons:
- I want to stay up-to-date on the most innovative technologies in the tech industry
- Machine Learning opens up a lot of opportunities for programming applications that I can't solve with simple code
Following is a chronoligical "journal" of my journey to achieving proficiency with Machine Learning. Here is a table of contents of what I've learned:
| Topic |
|---|
| Linear Regression |
| Regularized Logistic Regression |
-
Enrolled in and began Andrew Ng's Machine Learning Course on Coursera
- Finished Weeks 1 - 3
-
Worked on Kaggle's House Prices dataset
- Accuracy achieved on training data through Linear Regression: 92.6%
- Note for next time: Use Pandas for dataset manipulation
-
Worked on Kaggle's Titanic Survival dataset
- Accuracy on testing set through Regularized Logistic Regression: 74.2%