Sharing a demo of another small project I built using Python and Streamlit — a Seed Classification App 🌱 In this application, users can enter seed measurements like height, width, and thickness, and the system categorizes the type of seed based on these parameters. This project helped me understand how parameter-based classification logic and interactive UI components can be combined to build simple decision-support tools. It was a great exercise in turning numerical inputs into meaningful predictions using Python. Excited to keep building more data-driven applications! #Python #Streamlit #MachineLearningBasics #Classification #StudentDeveloper

New Post in my #TechnicalScripter2026 Series! I’ve published a new write-up on Error Handling in Flask, covering how proper exception handling helps build more reliable and production-ready web applications. Handling errors gracefully is an important step toward creating robust backend systems. 🔗 Read the post here: https://lnkd.in/gPvBXKJF Looking forward to your feedback and suggestions! #Python #Flask #BackendDevelopment #WebDevelopment #LearningInPublic

The more I work on backend systems, the more I realize how important clarity is. Not just in code — but in structure, naming, flow, and decision-making. Clean code doesn’t mean perfect code. It means understandable code. There’s always room to improve, refactor, and simplify. That continuous improvement mindset is what keeps engineering interesting. #BackendDevelopment #Python #Django #SoftwareEngineering

🚀 New Post in my #TechnicalScripter2026 Series! In this write-up, I compare Flask vs Django, two powerful Python frameworks, and discuss how developers can choose the right one based on project requirements and scalability needs. Choosing the right framework plays a key role in building efficient backend applications. 🔗 Read the post here: https://lnkd.in/g38YMU8j Looking forward to your thoughts and feedback! #Python #Django #Flask #BackendDevelopment #WebDevelopment #TechnicalScripter2026

Excited to share my latest write-up as part of my #TechnicalScripter2026 series! 🚀 In this post, I explore Flask vs FastAPI and discuss how to choose the right framework for backend API development. Would love to hear your thoughts and feedback! 🔗 Read here: https://lnkd.in/guCbibrs #Python #BackendDevelopment #LearningInPublic #Flask #FastAPI #TechnicalScripter2026

Today, I deepened my understanding of backend development using Python and Flask. What I learned: ✔️ How Flask handles routing ✔️ GET vs POST requests ✔️ Connecting frontend forms with backend logic ✔️ Basic project structure organization Understanding how data flows between client and server made the concepts much clearer. Step by step, I’m building a strong foundation in backend development. #Python #Flask #BackendDevelopment #WebDevelopment #LearningJourney

𝐅𝐮𝐧 𝐅𝐚𝐜𝐭 : When you execute "python app.py" sadly you actually don't run the "app.py" file that you put all your hardwork for the last few hours, instead you run a python interpreter which takes the "app.py" file as parameter so that it can read and execute it

🚀 Built a Rock–Paper–Scissors Game using Streamlit & Python! 🎮 I recently created a Rock✊–Paper🖐️–Scissors✌️ game using Streamlit where users can play against the computer in an interactive web app. 🔹 Key features of the project: User-friendly UI using Streamlit Random computer moves using Python’s random module Real-time game result (Win👍 / Lose👎 / Tie🤝) Visual feedback with success, error messages & balloons 🎈 Custom gradient background styling using HTML & CSS 🔹 What I learned: Building interactive web apps with Streamlit Handling user input using widgets like selectbox and button Applying game logic using conditional statements Enhancing UI with custom styling This project helped me strengthen my Python logic and understand how quickly we can turn ideas into web apps using Streamlit. 💡 Excited to build more interactive projects as I continue learning Python, FastAPI, and Data Science tools! #Python #Streamlit #BeginnerProject #WebApp #LearningByDoing #DataScience #Programming #PythonProjects

Built a House Price Prediction Web App using Python, Flask, and Machine Learning. From data preprocessing to a polished UI, this project predicts prices dynamically and makes ML feel interactive.

I’m building a stock prediction portal with Python, Django REST framework, and React to predict stock trends using machine learning. 🎯 Goals: Deliver accurate stock predictions Create a responsive web experience Build interactive visualizations Can’t wait to share updates as I make progress! 📈 #FullStackDevelopment #MachineLearning #Python #React #DjangoREST