𝗣𝗿𝗲𝗽𝗮𝗿𝗲 𝗳𝗼𝗿 𝗝𝗼𝗯 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀.

In DS or AI/ML interviews, you need to be able to explain models, debug them live, and design AI/ML systems from scratch. If you can’t demonstrate this during an interview, expect to hear, “We’ll get back to you.”

The attached person's name is Chip Huyen. Hopefully you know her; if not, then I can't help you here. She is probably one of the finest authors in the field of AI/ML.

She designed proper documentation/a book for common ML interview questions.

Target Audiences: ML engineer, a platform engineer, a research scientist, or you want to do ML but don’t yet know the differences among those titles.Check the comment section for links and repos.

📌 link:
https://huyenchip.com/ml-interviews-book/

#JobInterview #MachineLearning #AI #DataScience #MLEngineer #AIInterview #TechCareers #DeepLearning #AICommunity #MLSystems #CareerGrowth #AIJobs #ChipHuyen #InterviewPrep #DataScienceCommunit


https://t.me/CodeProgrammer 🌟

A new guide for preparing for technical developer interviews has been released. 😳

It covers key topics: design patterns, application architecture, best practices and clean code principles, algorithms and data structures, as well as typical questions on languages and technologies

✅more: https://github.com/DevCaress/guia-entrevistas-de-programacion

👉 https://t.me/CodeProgrammer

Google has updated its AI service NotebookLM, and this could really revolutionize online education.

Previously, the tool could create text summaries and podcast lessons from documents and links. Now there is a new feature — turning an article or documentation into a full video analysis. 😦

In the demo, Google showed how a regular article about JavaScript functions from MDN was transformed into a structured video review in seconds.

With this approach, learning becomes easier, more accessible, and more visual. It looks like a new era in online education is coming.

Try it: notebooklm.google

👉 @https://t.me/CodeProgrammer 🌟

Introducing Vanna: An Open-Source Text-to-SQL Tool | Daily Dose of Data Science posted on the topic | LinkedIn
Finally! A Text-to-SQL tool that actually works!

(100% open-source, 20k+ stars)

Vanna is an open-source RAG framework for complex Text-to-SQL generation, designed for handling dynamic datasets.

Works in 2 easy steps:

1️⃣ Train a RAG “model” on your data.
2️⃣ Ask questions in natural language which will return SQL queries that can be set up to automatically run on your database.

Key features:

🎯 High accuracy on complex datasets
🤖 Self-learning: improves with each query
🔒 Secure: data never leaves your environment
🌐 Connect to any SQL DB (Snowflake, Redshift, etc.)
🧩 Multiple front-end integrations (Jupyter, Slack, etc.)

Vanna GitHub: https://github.com/vanna-ai/vanna

https://t.me/CodeProgrammer 🌟

This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://t.me/addlist/8_rRW2scgfRhOTc0

✅ https://t.me/Codeprogrammer

Found a top open-source tool

It turns any JSON or YAML into an interactive mind-map.

Convenient for analyzing complex structures, you can immediately see connections and nesting.

The perfect tool to avoid getting lost in the "forest of brackets" and to understand data faster. A must-have for developers 😧

confmap.com

👉 @codeprogrammer