This hybrid search stack I mentioned in the post is actually implemented in this open-source context retrieval layer for agents.GitHub repo: https://t.co/iU6P0KoaRf ...

Vector search is not always the answer.A 30-year-old algorithm with zero training, zero embeddings, and zero fine-tuning still powers Elasticsearch, OpenSearch, and most production search systems today.It's called BM25, and it's worth understanding why it refuses to die.Let's say you're searching for "transformer attention mechanism" in a library of ML papers.BM25 scores documents using three core ideas:1) Word rarity matters more than word frequencyEvery paper contains "the" and "is" so those words carry n ...

15-16) Set max_workers and pin_memory in DataLoader.PyTorch dataloader has two terrible default settings. Update them according to your config.Speedup is shown in the image below 👇 https://t.co/BBuk5RSqLS ...

14) Use momentumIn gradient descent, every parameter update solely depends on the current gradient. This leads to unwanted oscillations during optimization.Momentum reduces this by adding a weighted average of previous gradient updates to the update rule.Check this 👇 https://t.co/77X9rwRyOF ...

I have been training neural networks for 10 years now.Here are 16 ways I actively use to optimize model training:(detailed explanation ...🧵) https://t.co/5HyMgEOIks ...

Generative vs. discriminative models in ML:(a popular ML interview question) https://t.co/fVVwZBkCVR ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):9 MCP, Agents, and RAG projects for AI engineers: https://t.co/fKTuaVMTc9 ...

Find all these projects in our AI Engineering Hub, along with 90 more hands-on projects: https://t.co/z9IxdiEm8w(don't forget to star it ⭐ ) ...

9 MCP, Agents, and RAG projects for AI engineers: https://t.co/fKTuaVMTc9 ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. https://t.co/AyKdh1l7ajAvi Chawla (@_avichawla):Microsoft.Google.AWS.Everyone's trying to solve the same problem for AI Agents:How to connect your agents to enterprise data without duct-taping a dozen tools together?Your data lives in Postgres, Snowflake, MongoDB, Gmail, etc, scattered across dozens of apps.Your AI https://t.co/huBady60vm ...