Yash Chaudhari @TimeToLearnAI
Learning AI/ML from scratch | Sharing daily concepts, code & struggles | Building in public | #100DaysOfML | DMs open Pune, India Joined November 2018-
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Tomorrow: More practice on Data Structures & Algorithms + revision. Follow @TimeToLearnAI for daily progress, code implementations, project builds, and the complete journey toward AI/ML mastery. What’s one algorithm or data structure you found tricky? Drop it below 👇 #100DaysOfML #Algorithms #DataStructures
Reflection: Day 8 was intense but super rewarding. Implementing algorithms myself made the concepts stick much better. I now have way more respect for how efficiently Python handles data under the hood. Consistency is paying off — slowly building strong fundamentals. 🔥
Day 8 Complete ✅ A heavy but extremely valuable day! Moved into Linear Data Structures and Algorithms — the real backbone of efficient programming and Machine Learning. Covered: • Big O Notation & Algorithm Analysis • Stacks, Queues, Linked Lists (Singly & Doubly) • Hash Maps / Sets • Dynamic vs Static Arrays #100DaysOfML #Python #DataStructures
Follow @TimeToLearnAI for daily project builds, code insights, and the complete journey from Python basics to AI/ML. Which OOP concept confuses you the most? Or which project should I try next? Drop your thoughts! 👇 #100DaysOfML #PythonOOP
Key Takeaways from Day 7: - Encapsulation helps protect and control data access - Inheritance + Polymorphism = massive code reusability - Abstraction makes complex systems much easier to manage - OOP is all about writing cleaner, more maintainable code
Day 7 Complete ✅ Deep dive into core Object-Oriented Programming concepts Covered: • Encapsulation (Getters & Setters) • Inheritance & Code Reuse • Polymorphism • Name Mangling • Abstraction Solid day strengthening OOP foundations. #100DaysOfML #Python #OOP
Reflection: After building these four projects, I can feel a noticeable jump in my coding confidence. Going from procedural code to thinking in classes is a game-changer. Slow but steady progress feels good. 💪
Key Takeaways: - OOP makes code much more organized and scalable - Special methods (__init__, __str__, etc.) are extremely powerful - Thinking in objects feels more natural now These concepts will be very useful later when building custom ML models and data pipelines.
Day 6 Complete ✅ Level up achieved! Today I entered the world of Object-Oriented Programming (OOP) — Classes and Objects. Covered: • Classes vs Objects • Methods & Attributes • Special (Dunder) Methods • Dynamic Attributes #100DaysOfML #Python #OOP
Follow @TimeToLearnAI for daily Python → AI/ML progress, code examples, and honest reflections. What was your biggest win this week? Let’s celebrate small wins together! 🚀 #100DaysOfML #PythonForDataScience
Reflection: Day 5 felt like a big step up in confidence. Going from basic scripts to handling data validation, patterns, and errors properly is exciting. The more I build, the more I realize how strong these fundamentals will make my future ML journey.
Day 5 Complete ✅ A massive progress! Covered a lot of ground and built several mini-projects. Python is starting to feel much more natural now. Covered: • Loops & Sequences • Dictionaries & Sets • Working with Modules • Error Handling & Debugging #100DaysOfML #Python
Next up: More practice + moving closer to data structures & libraries needed for Machine Learning. Follow @TimeToLearnAI if you’re on a similar journey. Drop your favorite mini-project idea below — I might build it soon! 👇 #100DaysOfML #LearnToBuild
This second round of Python basics is hitting differently — much deeper understanding and confidence compared to before. Grateful for the process. Slow and steady is winning. 💪
Day 4 Complete ✅ Today was all about leveling up — moved from basic scripting to writing reusable and organized code. Deeply covered: • Functions & Scope (Local vs Global) • Advanced String & Logic applications • Code organization and reusability #100DaysOfML #Python
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