💡 A complete package for success in data science and machine learning interviews!

👩🏻‍💻 I found a GitHub repo full of resources you need to succeed in Data Science and Machine Learning interviews!

❓ What do you find in it?

1⃣ Practical cheat sheets: Important tips gathered in one place.

🔢 Cool books: resources worth your time!

🔢 Frequently Asked Interview Questions: Topics that are asked in most interviews and that you are likely to encounter.

🔢 Portfolio projects: To make your resume stronger.


✅ In short, a complete package for preparing for data science interviews, without the confusion!

🔗 Here is the repost link: 👇

🔗 Cracking the data science interview

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https://t.iss.one/CodeProgrammer 🦾

🚀 80 Python Interview Questions with Answers & Code! 🚀

✅ Why this resource? 
- Covers frequently asked questions in Python interviews 

📄 Each question comes with detailed answers and ready-to-use code snippets, making it perfect for beginners and experienced developers alike. Whether you're preparing for a job interview or leveling up your Python skills, this guide has you covered! 👀 

🔥 Don’t miss out! Save this, share it, and start preparing today! 💼 

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https://t.iss.one/CodeProgrammer

💯 Top 100+ Google Data Science Interview Questions

🌟 Essential Prep Guide for Aspiring Candidates

Google is known for its rigorous data science interview process, which typically follows a hybrid format. Candidates are expected to demonstrate strong programming skills, solid knowledge in statistics and machine learning, and a keen ability to approach problems from a product-oriented perspective.

To succeed, one must be proficient in several critical areas: statistics and probability, SQL and Python programming, product sense, and case study-based analytics.

This curated list features over 100 of the most commonly asked and important questions in Google data science interviews. It serves as a comprehensive resource to help candidates prepare effectively and confidently for the challenge ahead.

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https://t.iss.one/addlist/0f6vfFbEMdAwODBk