Top Tweets for #100daysofML
#100DaysOfCode/#100DaysOfML day 91
ML - started classification, logistic regression.
DSA - started binary search tree=> basics and implementation. Level order, preorder, inorder, postorder traversal using recursion
solved-> insert in bst, search in bst.
#LearnInPublic #DSA
Day 5/100 of #100DaysOfML ✅
Learned APIs & Web Scraping in Python.
• API requests with requests
• Web scraping using BeautifulSoup
• Turning web data into datasets
• Converting web data into datasets
🔗 Notebook:
https://t.co/XtMBTWhsKG
100 Days of ML | Day 33 🚀
Learned about Handling Mixed Variables in Feature Engineering. 📊
Real-world datasets often contain a mix of:
• Numerical features
• Categorical features
• Missing values
#100DaysOfML
Day 1/100 of Learning Machine
Learning in Depth 🚀
Started my 100-day Machine Learning journey today.
📚 Topics covered: • Python Revision • NumPy Fundamentals • Pandas for Data Analysis • Matplotlib for Data visualization
#MachineLearning #100DaysOfML #LearnInPublic
Day 4/100 of #100DaysOfML ✅
Learned how to work with JSON in Python today.
• Reading JSON files
• Parsing nested data
• Converting JSON to Python objects
• Handling structured data for ML workflows
🔗Notebook
https://t.co/3rlVJKRcyq
#100DaysOfCode/#100DaysOfML day 90
ML - feature engineering, polynomial regression; EDA project- data cleaning done, actual eda started
DSA-
solved-> Path sum, Path sum II, flatten binary tree into Linked List
Gym- Chest, triceps
(played teen-patti with cousins)
#LearnInPublic
Day 4/100 of #100DaysOfML ✅
Learned how to work with CSV files in Pandas:
• Loading from files & URLs
• Missing values & parsing errors
• Date parsing
• Large datasets
• Encodings & converters
•Framing the problems
🔗Notebook:
https://t.co/u91pHAyIcz
Got a PR merged into pytorch/torchtitan
CI was failing — torchcomms manages TP process groups outside c10d registry, so torch.compile couldn't resolve them at runtime
skipped the flavor to unblock CI until the real fix lands in torchcomms
#100DaysOfML #pytorch #opensource
#100DaysOfCode/#100DaysOfML day 89
ML - feature scaling, checking gradient descent for convergence, choosing a good learning rate, lots of eda project work
DSA-
solved-> binary tree paths, sum of longest bloodline,
Lowest common ancestor(LCA) in binary tree
#LearnInPublic #DSA
Day 3/100 of #100DaysOfML ✅
Learned about Tensors today:
• 0D to 5D Tensors
• Rank, Shape & Size
• Applications in NLP, CV & Video Processing
Built my first end-to-end ML project: a placement predictor using IQ, CGPA & Logistic Regression.
🔗Project
https://t.co/15yR28p1A8
Random CV on time series = data leakage. Model trains on Nov, tests on Oct. It sees the future.
TimeSeriesSplit fixes this — train on past, test on future only, Switched to it mid-project. Validation loss jumped, predictions got real.
Worse CV score. Better model.
#100DaysOfML
#100DaysOfCode/#100DaysOfML day 88
ML - multiple linear regression, vectorization and gradient descent for multiple features, some eda work
DSA-
solved-> zigzag order traversal, constructing b.t from inorder and postorder traversal
Gym- back, biceps
#LearnInPublic #DSA
Day 2/100 of #100DaysOfML ✅
Today I explored:
• Applications of Machine Learning
• ML Development Life Cycle
• Data Engineer vs Data Analyst vs Data Scientist vs ML Engineer
Building a stronger foundation before diving deeper into the technical side. 🚀
#MachineLearning #AI
#100DaysOfCode/#100DaysOfML day 87
ML - updating parameters using gradient descent, env setup and started my first eda project
DSA-
solved-> binary tree pruning, symmetric tree
tried->zigzag traversal
(which platform do you use for data analysis??)
#LearnInPublic #DSA
Day 1/100 of #100DaysOfML ✅
Covered the fundamentals today:
• What is ML?
• AI vs ML vs DL
• Types of ML
• Batch vs Online Learning
• Challenges & Applications
Onward. 🚀
#100DaysOfCode/#100DaysOfML day 86
ML -cost function, its visualization wrt the parameter values, started eda on netflix dataset.
DSA-
->Univalued binary tree
->max binary tree (O(n^2) solution but did it myself)
Gym- Legs & shoulders
#LearnInPublic #DSA
LIKE. SHARE. SUBSCRIBE
100 Days of ML | Day 31
Learned about Power Transformations for making data more Gaussian-like and improving model performance.
• Box-Cox Transform → works on positive values only
• Yeo-Johnson Transform → works with both positive and negative values
#100DaysOfML
A few months ago, I completed a 100 Days of Code challenge.
It taught me that progress doesn't come from motivation - it comes from showing up consistently.
Starting tomorrow, I'm taking on a new challenge:
100 Days of Machine Learning.
One day at a time.🚀
#100DaysOfML
The more I learn about Machine Learning, the more I realize that training the model is just one small part of the process.
There's so much happening behind the scenes with data, deployment, and making things work reliably.
Still learning, one step at a time.
#100DaysOfML
#100DaysOfCode/#100DaysOfML day 83
ML - completed all pending lectures, labs, assignments of the stats and prob. course and FINALLY COMPLETED THE MATHS FOR ML AND DS SPECIALIZATION COURSE SERIES
DSA - solved balanced binary tree problem
Gym - back & biceps
#LearnInPublic #DSA
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