Hello, everyone! I'm Deepak, and I'm excited to share my journey into the world of Machine Learning. Right now, I'm in the fourth week of my course, and we're delving into Binary Classification.
Starting from Scratch
- When I began this journey, I didn't know much about Machine Learning. But as I continue, I'm starting to understand it better.
Binary Classification: What Is It?
- In the fourth week of my course, we're focusing on Binary Classification. It's all about putting data into one of two categories, like yes/no or positive/negative.
My Progress So Far
Here's what I've covered:
K-Nearest Neighbor Classification
Distance Metrics and Cross-Validation
Computational Efficiency of KNN
Introduction to Decision Trees
Level Splitting
Measuring Impurity
What's Coming Up
Next, I'll be exploring:
Entropy and Information Gain
Generative vs Discriminative Models
The Naive Bayes Classifier
Conditional Independence
How to Classify Test Points
Wrapping It Up
- In conclusion, I'm having a great time learning Machine Learning. From the basics of K-Nearest Neighbor Classification to more advanced topics like Decision Trees, I'm making progress. Stay tuned for more insights as I explore Binary Classification and these exciting new topics. There's so much more to learn, and I'm eager to share it with you!