repo2nb Simplifies Kaggle Project Workflow

Excited to share that I’ve deployed my House Price Predictor app live. This project uses Python, pandas, scikit-learn, and Streamlit to predict house prices based on: number of bedrooms number of bathrooms property size in m² Through this project, I learned more about: data preprocessing feature scaling training a machine learning model saving and loading model files using GitHub for version control deploying a live app with Streamlit Live app: https://lnkd.in/gcHr2ctQ This is part of my Data Science and Machine Learning learning journey, and I’m looking forward to building more projects. #Python #DataScience #MachineLearning #Streamlit #GitHub #LearningJourney

I got tired of choosing between Python's simplicity and Rust's speed. So I stopped choosing. I've been building rmath; a high-performance math toolkit for Python with a pure Rust core, bridged through PyO3. Phase 1 just shipped. Here's what that means: 61 functions. Scalar arithmetic to 3D geometry to bit-level integer math. Not just working - standard library grade. Every function has Google-style docs, .pyi type stubs so VS Code treats it like a native library, and 100% test coverage verified against Python's own math module. The part that surprised me most? Writing Rust that feels invisible to the Python developer using it. That's the real engineering challenge; not the performance, the seamlessness. Phase 2 is next. Vectorized operations and statistics. Things are about to get faster. Have you ever built a Python extension in Rust? What broke first? #Python #Rust #PyO3 #SoftwareEngineering #OpenSource

💭 Day 6 with Python… it finally felt useful. Until now, I was learning concepts… Conditions, loops, functions… all great. But today, something changed. 👉 I learned about lists. At first, it looked simple: A collection of values in one place. But then I realized… This is how real-world data is handled. Names. Numbers. Marks. Tasks. Everything can be stored, accessed, and managed easily. 💡 Instead of writing separate variables like: name1, name2, name3… I could simply do: 👉 names = ["A", "B", "C"] Cleaner. Smarter. Scalable. So I tried something small 👇 🚀 Mini use-case: I created a list of numbers ✔ Found the largest number ✔ Calculated the sum ✔ Even filtered values And suddenly… It didn’t feel like practice anymore. It felt like solving real problems. 🐍 That’s when it clicked: Python isn’t just for coding exercises… It’s for handling real data in real situations. ✨ From concepts → to practical thinking This journey is slowly becoming meaningful. #Python #CodingJourney #Day6 #Lists #DataHandling #LearnToCode #ProgrammingLife #TechSkills #Growth 🚀

🐍 Day 8 of Learning Python — and things are getting real! Today's lab was all about writing code that doesn't break (or at least fails gracefully 😄). Here's what I worked through: ✅ Exception Handling — try / except / else / finally • Caught ZeroDivisionError, FileNotFoundError, ValueError, and TypeError • Used `raise` to throw custom error messages • Built my own exception class: TooSmallError 🎉 ✅ Standard library deep dive: • math — calculated circle areas, factorials, GCD, and compound interest • random — shuffled lists, simulated 1000 coin flips, generated reproducible sequences with seed() • datetime — parsed date strings, added time deltas, sorted ISO dates, and printed 5-day schedules ✅ Introspection with dir() and help() The biggest lesson today? Real-life programs don't always get perfect input. Learning to handle errors gracefully is just as important as writing the happy path. Day by day, the pieces are coming together. 💪 #Python #100DaysOfCode #LearningToCode #PythonProgramming #CodingJourney #Day8

Stuck in tutorial hell? 🐍 The best way to actually master #Python is to build #projects that challenge your current level. Here are 12 #project ideas to help you level up: 🟢 #Easy: Focus on logic and basic syntax with a URL Shortener or a CLI Utility. 🟡 #Mid: Build real-world logic with a Weather App or a Blog Application. 🔴 #Pro: Dive into advanced tech like Image Recognition or AI Chatbots. Best practice? Don't just follow a tutorial add one custom feature of your own to make it unique! 💡 💾 Save this roadmap for your next coding session! 👇 Comment which project you’re going to build next. Follow for more Python & Data Science tips 🚀 #Python #Coding #DataScience #ProjectIdeas #Programming #PythonLearning #TechCareer

🚀 Day 11 – File Handling in Python Today I learned how Python works with files — one of the most practical concepts in real-world applications. 🔹 Files help store data permanently 🔹 We can read, write, and update data anytime 📌 File Modes: • 'r' → Read • 'w' → Write (overwrites file) • 'a' → Append (adds data) • 'x' → Create new file 💡 Best Practice: Using with statement automatically closes the file. 📌 Example: with open("data.txt", "r") as file: content = file.read() print(content) 🔥 Key Learning: File handling is used in logs, reports, user data storage, and real-world applications. Ajay Miryala 10000 Coders #Python #FileHandling #CodingJourney #100DaysOfCode

📊 Day 27: Getting Started with Matplotlib As part of my continuous learning journey, I’m diving into Matplotlib — one of the most powerful data visualization libraries in Python. 🔹 What is Matplotlib? It’s a plotting library used to create static, animated, and interactive visualizations in Python. 🔹 Why it matters: - Turns raw data into insights - Helps communicate findings clearly - Widely used in Data Science & Engineering 🔹 First example: import matplotlib.pyplot as plt x = [1,2,3,4] y = [10,20,25,30] plt.plot(x, y) plt.title("Simple Line Plot") plt.xlabel("X-axis") plt.ylabel("Y-axis") plt.show() 📌 Simple, but powerful. This is the foundation of data visualization in Python. Tomorrow: Customizing plots 🎯 #M4ACELearningChallenge #LearningInPublic

Most Python learners don’t struggle with syntax. They struggle with what comes next. 🐍 If you're serious about moving from learning Python → applying Python, this is for you. 📌 Save this for later — you'll thank yourself during your first project #Python #PythonForBeginners #DataScience #Programming #LearnPython #NumPy #Pandas #DataAnalytics #Coding #TechCareers