🚀 Exploring APIs with Postman!

Just wrapped up some great tutorials on using variables and building dynamic requests in Postman. Super helpful for streamlining API testing!
📘 Postman Docs https://learning.postman.com/docs/sending-requests/variables/variables/

🎥 YouTube Tutorial [https://www.youtube.com/watch?v=IjVVQmQIiBg]

Today's challenge on LeetCode: Patients With a Condition 🏥🔍

Hint: Use .contains() with regex to handle variations

Give it a shot! [https://leetcode.com/problems/patients-with-a-condition?envType=study-plan-v2&envId=30-days-of-pandas&lang=pythondata] How did you approach it? 👇
#Python #Pandas #DataScience #LeetCode

🚀 Getting into recommendation systems? Content-based filtering is a powerful approach that suggests items based on user preferences and item attributes. Unlike collaborative filtering, it doesn’t need a huge user base to work effectively!

🔍 Google’s ML guide breaks it down with key concepts & best practices: developers.google.com/machine-learning/recommendation

#MachineLearning #RecommendationSystems #AI

Sharpening my coding skills with LeetCode! 🧠💻 Try this SQL + Regex challenge: Find users with valid emails. Can you solve it? 👀

🔗 https://leetcode.com/problems/find-users-with-valid-e-mails?envType=study-plan-v2&envId=30-days-of-pandas&lang=pythondata 💡 Need a hint? Here you go: https://leetcode.com/problems/find-users-with-valid-e-mails?envType=study-plan-v2&envId=30-days-of-pandas&lang=pythondata
#LeetCode #SQL #Regex

🚀 Why loc in pandas is faster than subsetting:

⚡ Direct label access (no recalculations)
💾 View vs. Copy (loc returns a view, subsetting makes a copy)
⚙ Cython-optimized for speed
🏃 Less overhead in chained ops

#Python #DataScience #pandas

PDF: Given a model, how likely is the data?
Likelihood: Given the data, which model parameters make it most probable? This is key in ML models like Logistic Regression using MLE for parameter tuning.

👉 Learn: https://www.geeksforgeeks.org/probability-density-estimation-maximum-likelihood-estimation/#

#MLE #MachineLearning #AI #DataScience

Unlock the power of Exploratory Data Analysis (EDA) to make smarter decisions and uncover hidden insights!

[https://www.ibm.com/think/topics/exploratory-data-analysis]

#DataScience #EDA #Analytics