Uploaded January 2026 | Updated September 2026, 2 days ago
The #1 mistake in Machine Learning? 🤫 It’s NOT the algorithm.
Want to build an AI model that actually works? Forget the magic. It’s all about these 4 disciplined steps—plus the metrics you must know.
🚨 Quick Model Building Blueprint:
Define the Problem: What are you actually solving?
Data Detective Work: Feature Engineering is key! 🕵️♀️
Train & Validate: Model Selection is all about your data’s "personality."
Deploy & Monitor: The job's not done until it's live.
🔥 Pro Tip: Missing data? Don't just use the mean/median! Learn the better ways to handle it, like Predictive Imputation or Flagging the missing values themselves.
Check out stratascratch.com to practice hundreds of real-world data science and machine learning problems!
Which metric is your favorite? Let me know in the comments! 👇
#MachineLearning #AIShorts #DataScience #DataAnalyst #CodingTips #TechHacks #Python #DeepLearning #MLTips #CareerAdvice
The #1 mistake in Machine Learning? 🤫 It’s NOT the algorithm.
Want to build an AI model that actually works? Forget the magic. It’s all about these 4 disciplined steps—plus the metrics you must know.
🚨 Quick Model Building Blueprint:
Define the Problem: What are you actually solving?
Data Detective Work: Feature Engineering is key! 🕵️♀️
Train & Validate: Model Selection is all about your data’s "personality."
Deploy & Monitor: The job's not done until it's live.
🔥 Pro Tip: Missing data? Don't just use the mean/median! Learn the better ways to handle it, like Predictive Imputation or Flagging the missing values themselves.
Check out stratascratch.com to practice hundreds of real-world data science and machine learning problems!
Which metric is your favorite? Let me know in the comments! 👇
#MachineLearning #AIShorts #DataScience #DataAnalyst #CodingTips #TechHacks #Python #DeepLearning #MLTips #CareerAdvice
![Solving Complex SQL Interview Questions [How to organize lengthy code solutions]](https://i.ytimg.com/vi/vLjAG9eXkcU/mqdefault.jpg "Solving Complex SQL Interview Questions [How to organize lengthy code solutions]
Lets talk about a framework to organize lengthy SQL code on a data science interview or on the job. Most data science problems involve numerous business rules and deal with complicated logic. Your code might end up being hundreds of lines long. How do we properly organize our solution? I lay out a framework that can help anyone.
Link to the question: https://platform.stratascratch.com/coding/9701-3rd-most-reported-health-issues?python=null&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
This series is for both beginner and intermediate data scientists and analysts interested in learning how to solve common data science interview questions in SQL. These are real data science interview questions.
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Timestamps:
Intro: (0:00)
4 Tips on Approaching Writing Lengthy Code: (1:35)
Interview Question: (4:50)
Exploring the Data: (5:20)
Writing Out the Approach: (5:58)
Solution: (7:20)
Conclusion: (13:25)
About The Platform:
Im using StrataScratch, a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com")
![[Part 2] EDGE Cases in Data Analysis: How to Reduce the Risk of Missing Important Details](https://i.ytimg.com/vi/vQmk0bH25d0/mqdefault.jpg "[Part 2] EDGE Cases in Data Analysis: How to Reduce the Risk of Missing Important Details
In this video, you will learn how considering the EDGE cases help in data analysis to reduce the risks of missing important details.
Part 1: https://www.youtube.com/shorts/rEaSskQhId4
👉 Watch the full video: https://youtu.be/yQSZT65WET4
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#EDGEcase #DataAnalysis")
