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!