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01 Enjoy our content? Advertise on this channel and reach a highly engaged audience! 👉🏻
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02 Data Science Techniques | 509 | 5 | Loading... |
03 Important Data Terms | 744 | 7 | Loading... |
04 Statistical models cheatsheet | 722 | 7 | Loading... |
05 Media files | 861 | 6 | Loading... |
06 Statistical distributions cheatsheet | 812 | 2 | Loading... |
07 Career Path of A Data Analyst | 1 366 | 10 | Loading... |
08 Flow chart of commonly used statistical tests | 1 500 | 10 | Loading... |
09 Introduction to Probability and Statistics for Engineers
List of probability and statistics cheatsheets by Stanford | 1 670 | 18 | Loading... |
10 Brain of an AI Engineer | 2 074 | 20 | Loading... |
11 [Compilation]1000+ Data Science Interview Questions/Preparation Resources
Compilation created by kaggle users
1. GIT interview questions for DS and SQL Interview questions
2. 50 ML questions
3. Four years on interview questions
4. Compilation of pandas interview questions
5. Difference between common ML algortihms
6. Scenario based Data questions
7. Top python interview questions
8. Internship questions for DS interns
9. Questions from DS- Netflix
10. India specific Data science interview questions
11. R interview questions
12. Explain a project in Data science
13. A great collection of cheatsheets, analyzed here
14. A collection of questions on Github here
15. Cheat Sheets for Machine Learning Interview Topics
16. Compiled list of 600+ Q&As for Data Science interview prep 🎉
17. Approaching almost any ML Problem, originally shared on Kaggle
18. A Basics refresher
19. A notebook
20. Companies and Data Science Interview questions Megathread
21. Data Scientist - Interview Question Bank
22. ML Interview questions
23. Machine Learning Interviews Book
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https://www.kaggle.com/discussions/questions-and-answers/239533
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👉Join @datascience_bds for more👈 | 1 953 | 34 | Loading... |
12 The LLM Scientist Roadmap | 1 571 | 22 | Loading... |
13 LLMOps vs MLOps | 1 897 | 21 | Loading... |
14 Design patterns for AI Agentic workflow in LLM applications | 2 068 | 14 | Loading... |
15 For all Data Engineers out there, here is The State of Data Engineering 2024
Some of the highlights:
✅ More and more, data observability tools are used not just to monitor data sources, but also the infrastructure, pipelines, and systems after data is collected.
✅ Companies are now seeing data observability as essential for their AI projects. Gartner has called it a must-have for AI-ready data.
✅ Like in 2023, Monte Carlo is leading in this area, with G2 naming them the #1 Data Observability Platform. Big organizations like Cisco, American Airlines, and NASDAQ use Monte Carlo to make their AI systems more reliable. | 5 267 | 33 | Loading... |
16 5 Leading Small Language Models of 2024 | 1 854 | 11 | Loading... |
17 Data Analytics in 5 steps | 2 106 | 10 | Loading... |
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Introduction to Probability and Statistics for Engineers
List of probability and statistics cheatsheets by Stanford
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