JSON prompting for LLMs, clearly explained: ...

RT Avi Chawla (@_avichawla)9 MCP, Agents, and RAG projects for AI engineers: https://t.co/glppKndo1c ...

Industry Focus - The industry emphasizes sharing insights and tutorials on Data Science (DS), Machine Learning (ML), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAGs) [1] - The industry encourages users to reshare insightful content within their networks [1]

Find all these projects in our AI Engineering Hub, along with 70 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/glppKndo1c ...

RT Avi Chawla (@_avichawla)I never use Pandas' describe method.Skimpy is a much better (and open-source) alternative that provides a comprehensive data summary, including data shape, column data types, stats, distribution chart, etc. https://t.co/i19N6BdUgs ...

Data Analysis Tools - The industry suggests using Skimpy as a superior open-source alternative to Pandas' describe method for comprehensive data summarization [1] - Skimpy offers detailed data insights, including data shape, column data types, statistics, and distribution charts [1]

Feature scaling is not always necessary in ML.Logistic regression (trained using SGD), SVM, MLP, and kNN classifiers usually do better with feature scaling.Tree-based models, Naive bayes, and Gradient Boosting are unaffected. https://t.co/vzy2RzLBW8 ...

@semanticbeeng on bi-temporal 👆 ...

RT Avi Chawla (@_avichawla)RAG can’t keep up with real-time data.Airweave builds live, bi-temporal knowledge bases so that your Agents always reason on the freshest facts.Supports fully agentic retrieval with semantic and keyword search, query expansion, and more across 30+ sources.100% open-source. https://t.co/0ne2MeCLbY ...