You're in an ML Engineer interview at Apple.The interviewer asks:"You have to build an ML-based face unlock system for iPhones.How would you train the model?"You: "I will capture user's images & train a binary classifier on them"Interview over.Here's what you missed:There are multiple issues with capturing user's images and training a clasifier.> Firstly, you'd need to on-device training, which can be expensive.> All images provided by the user will be "Class 1" samples. To train a binary classifier, where ...

RT Avi Chawla (@_avichawla)JSON prompting for LLMs, clearly explained: ...

That's a wrap!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):JSON prompting for LLMs, clearly explained: ...

To summarise:Structured (JSON) prompting for LLMs is like writing modular code; it brings clarity of thought, makes adding new requirements effortless, & creates better communication with AI.It's not just a technique, but rather evolving towards a habit worth developing for cleaner AI interactions. ...

JSON prompting for LLMs, clearly explained: ...

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

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. ...

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 ...