Life Learner | Masters of Applied Data Science @ University of Michigan | AI, Data Science, and Machine Learning
Views expressed are my own.
🚀 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]
🔧 Just wrapped up the Feature Engineering course on Kaggle! From transforming raw data to crafting powerful signals, this course sharpened my ability to unlock hidden patterns and boost model performance. #MachineLearning #DataScience #Kaggle
📊 New to time series forecasting?
Learn ARIMA modeling in this clear, hands-on guide from DataCamp!
Perfect for data science beginners.
🔗 https://www.datacamp.com/tutorial/arima
#ARIMA #TimeSeries #DataScience #Forecasting
Ever wonder how neural networks actually learn? It all starts with a simple but powerful concept from calculus: the chain rule.
📚 Dive in and level up your math game:
👉 https://machinelearningmastery.com/the-chain-rule-of-calculus-for-univariate-and-multivariate-functions/
#MachineLearning #DeepLearning #Backpropagation #NeuralNetworks #DataScience #AI
@barubary that's not the point
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
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
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/#
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]
🚀 Want to break into cloud computing? My latest article dives into earning AWS & Azure certifications—what to study, how to prep, and why it matters! ☁️📜
If you're looking to boost your career in cloud engineering, DevOps, or data, these certs can open doors. I share my learning path, key resources, and insights from my own journey.
Check it out here: https://godot107.github.io/projects/cloud_learning_journey/
#CloudComputing #AWS #Azure #Certification #CareerGrowth #TechLearning
🚀 New Article: Dive into sentiment analysis of Amazon reviews using TF-IDF and Logistic Regression! Learn how to extract insights, balance classes, and boost model performance. 📖 Read: [https://medium.com/@manwill/sentiment-analysis-with-tf-idf-and-logis0tic-regression-f4cd86f359a1] #DataScience
Too much bias? Model underfits. Too much variance? Model overfits. The key is balance—generalizing well to new data.
Great breakdown here: Machine Learning Mastery https://machinelearningmastery.com/gentle-introduction-to-the-bias-variance-trade-off-in-machine-learning/
Building a sentiment analysis model using GloVe word embeddings! Excited to see how pre-trained vectors capture word meaning to improve accuracy. #AI #NLP #MachineLearning #GloVe
Machine Learning 101: A Glossary for Everyone!
Whether you're new to ML or brushing up on key concepts, this glossary from DeepAI is a fantastic resource! It covers everything from activation functions to zero-shot learning in an easy-to-understand way.
https://deepai.org/machine-learning-glossary-and-terms/machine-learning
🚀 Excited to launch my personal website[https://godot107.github.io/]!
Explore my journey in data, AI, and machine learning, discover projects from my GitHub, and dive into blogs about family plus more
Check it out and let me know what you think! 🌟 #AI #DataScience #PersonalWebsite
As an expecting father, I am imagining what family looks like. I liked how one dad mentioned 'we-time, before me-time.' It's a reminder to prioritize quality time over quantity, as it's so easy to be disengaged. #Fatherhood #ParentingJourney #FamilyFirst [https://open.spotify.com/episode/0Nmqqwat5Y04oVpW7nrusi?si=1BYbCz8LRciQeipH2vKKUw]
Build your personal website with GitHub Pages—free and easy! Fork a template, enable GitHub Pages in settings, and customize with Markdown, HTML, or Jekyll.
Need help? Watch Spencer Pao's guide: How to Create a Personal Website Using GitHub Pages: www.youtube.com/watch?v=g6AJ...