Welcome to The Backprop

Hello, and welcome to The Backprop Blog! 🤖

I created this blog with the vision of making machine learning accessible to everyone, no matter their background. Whether you’re an expert in statistics and mathematics or a high school student with a strong passion for learning, this blog is for you. Trust me, I know what it’s like to get all dizzy while trying to understand some complex topics.

Here, I’ll cover topics ranging from the essential linear algebra, derivatives, and more cutting-edge research. With this broad scope, The Backprop Blog aims to be a reliable and complete learning resource for ML enthusiasts.

Categories

The blog will be divided into four main categories:

• Theory
• Practical
• GPU Stuff
• Discussions

Theory

This category is all about ML theory: linear algebra, machine learning concepts, and techniques. From classic machine learning to modern deep learning theory, this section is the foundation of knowledge. Expect in-depth explanations, breakdowns of essential papers, and discussions on novel research.

Practical

This category is for hands-on learning. You’ll find Python code alongside explanations,
covering everything from basic SVMs to fine-tuning large language models. I’ll also include essential concepts related to libraries, optimizations, and more.

GPU Stuff

This section will cover GPU-related topics, including What is CUDA? and other fundamental concepts. It’s not the blog’s main focus, but I’ll include content here whenever it makes sense.

Discussions

This category is for open discussions, where you and I can create topics, share opinions, and solve doubts. Think of it like GitHub issues! (Yep, I’ll try to mimic that format while keeping this a static website… wish me luck 😅) I hope this section helps us refine, expand, and deepen our understanding of ML while fostering collaboration. (Long live open-source!)

Comments

Yes, every post will have a comment section at the end! You’ll be able to read and write comments using your GitHub account, simple and easy. Use these sections to ask questions, engage with fellow ML enthusiasts, and report any mistakes in the blog (e.g., typos, math errors, incorrect explanations, etc.).

What Else?

• Not seeing all these features yet? Don’t worry! I’ll be updating the blog in my free time.
• Have a topic you’d like me to cover? Reach out! You’ll find my contact info in the About Me section.
• Want to collaborate? Contact me! I’m open to collaboration.

Final Note

Wrapping things up, this blog aims to explain ML in an easy-to-follow way.
Some posts will go deep into concepts, while others will stay at a high level when necessary.
The main goal? To make learning machine learning clear, approachable, and engaging.

To current and future readers, thank you for being here.
Enjoy The Backprop Blog!

— Lucas Martinez

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