Machine Learning Pills

For anyone ready to master RL, this book seems to cover it all—from foundational principles to the latest methods used in real-world industry! It will be released by the end of this week! 👇 packtpub.com/en-us/product/d…

I've just started reading the early review copy of "Deep Reinforcement Learning Hands-On" by Maxim Lapan, a practical guide packed with advanced applications! Here’s what makes it a standout read 🧵 👇

Learn more about snoop bias in this week's 💊 Pill👇 substack-proxy.glitch.me/art…

Be careful with cross validation 👇

Check it out here: substack-proxy.glitch.me/art…

The steps of any Data Science project 👇

EDA clearly explained 👇

Multi Query, an Advanced Retrieval Strategy for RAG, clearly explained 👇

K-Nearest Neighbors clearly explained 👇

There are several types of data distributions you might encounter in a dataset. Here are some common ones 👇🧵

🚨NEVER split your data randomly! At least when working with Time Series data... Learn here what are the dangers of doing so 🧵 👇

Retrieval refers to the process of finding and extracting relevant information or documents from a large collection or database in response to a query or information need. Discover more 🧵 👇

Let's discuss another retrieval method: "Maximum Marginal Relevance" or MMR. 👉 MMR balances relevance and diversity in search results. Let's learn more about it 🧵 👇

📚 I've just read "Transformers for Natural Language Processing and Computer Vision" by Denis Rothman. A must read that offers deep insights into transformer architectures and their practical applications in NLP and computer vision. 🧵👇