Credit Card Default Prediction App with Machine Learning

Python: The Brain Behind Your Favorite Apps Ever wonder how apps "know" exactly what you need? Python is the engine under the hood of the world’s smartest websites, using AI to create personalized experiences just for you. From recommending your next favorite movie to providing instant customer support, it’s the technology making the web feel more human. Discover how we’re building a smarter digital world at Artemee.com!

🚀 Just built a Movie Recommendation System using Python! I recently worked on a project where I developed a Movie Recommender System that suggests similar movies based on user selection. This project helped me understand how recommendation engines work behind the scenes. 🔹 Tech Stack: * Python (Pandas, Pickle) * Streamlit (for interactive web app) * Similarity Matrix (Content-Based Filtering) 🔹 Features: * Select any movie from the list * Get top 5 similar movie recommendations instantly * Clean and simple user interface This project strengthened my concepts in data processing, recommendation systems, and building real-world applications. Looking forward to improving this further by integrating APIs, adding movie posters, and enhancing the UI! #Python #DataScience #MachineLearning #Streamlit #Projects #LearningJourney #AI

🏡 House Price Prediction App! I developed a Machine Learning-based web app using Python & Streamlit that estimates house prices based on important factors such as: ✔️ Area (in square feet) ✔️ Number of bedrooms ✔️ Property age ✔️ Distance from the city center ✨ Highlights of the project: Interactive and clean UI built with Streamlit Easy-to-use input fields for users Integrated ML model for accurate predictions Instant results display 🎯 What I learned while building this: Data cleaning & preprocessing techniques Working with regression algorithms Deploying ML models into web apps Designing simple and effective user interfaces 🛠️ Tech Stack: Python | Pandas | NumPy | Scikit-learn | Streamlit 🔗 Check out the project here: https://lnkd.in/ghhUHEGM 💡 Next improvements I’m working on: 🔹 Enhancing model performance 🔹 Adding visual analytics & charts 🔹 Improving UI with advanced features #MachineLearning #Python #AI #DataScience #Streamlit #Projects #BuildInPublic #Learning

I built a House Price Prediction App that estimates property prices based on key features such as lot area, construction year, overall condition, basement size, and location-related attributes. 🔧 Tech Stack: Python, Pandas, NumPy Scikit-learn (model development) Streamlit (interactive web application) 💡 Key Learnings: Data preprocessing: handling missing values and encoding categorical variables Maintaining feature consistency between training and prediction Building an end-to-end ML workflow (data → model → UI) Debugging practical issues like feature mismatches and NaN values 🖥️ The app provides a simple interface where users can input property details and get an instant price prediction. This project helped me move beyond theory and understand how to turn an ML model into a working application. 🔗 GitHub: https://lnkd.in/gGtxMZRa #MachineLearning #DataScience #Python #AI #Streamlit #LearningByDoing

🚀 Built my own “Hello Jarvis” assistant using Python I’ve been experimenting with voice & gesture-based automation, and this project brings a simple but powerful idea to life: 👏 With just two claps, the system triggers actions like opening a YouTube video instantly. 💡 What’s behind it: Python for core logic and automation Sound detection for clap recognition Integration with browser actions Built to work on macOS and Windows Supported by tools like Claude and Cursor for faster development 🔜 What’s next: I’m currently working on integrating voice command detection (e.g., “Hey Jarvis”) using Python speech recognition libraries to make the interaction even more natural and hands-free. 🎯 Why this matters: This is a step toward more natural human-computer interaction—moving beyond clicks and typing into voice and real-world signals. Excited to keep building more AI-driven automation projects and push this further 🚀 #Python #Automation #AI #MachineLearning #DataEngineering #VoiceAI #TechProjects #Portfolio

AI is reshaping the future of Python and web development. From AI coding assistants to smart web apps, developers who combine Python, full-stack skills, and AI tools will lead the next wave of innovation. Top trends in 2026: • AI Coding Agents • FastAPI + AI APIs • Smart Web Applications • AI Automation • RAG Applications Python + Web + AI is a powerful combination. #Python #WebDevelopment #AI #FullStackDeveloper #FastAPI #Tech

QR codes are everywhere — payments, menus, tickets… So I explored the logic behind how they actually work 👨💻 I’ve written an article on generating QR codes using Python, along with real-world applications and implementation. If you're a beginner or working on projects, this might be helpful! 💡 Read here: https://lnkd.in/g6WXwUgQ Would love your feedback 🙌 #Python #Programming #Developers #TechCommunity #Learning #Coding

Learn how to build a chatbot with Python and Dialogflow, and discover the benefits and applications of chatbots in various industries, including customer service and e-commerce. https://lnkd.in/g9bfE37N #Chatbot Read the full article https://lnkd.in/g9bfE37N

Built a tiny app that turns Python logic into modern C++ using Google Gemini. Backend: FastAPI + google.generativeai, frontend: React + Vite. It can also execute Python snippets locally and return output instantly. Great for prototyping algorithm translation workflows and learning C++ from Python code. Open to feedback and feature ideas!

I saw someone asking the Maccas app how to reverse a linked list. The result? A perfect, monster-level Python script. It turns out the assistant is running on Opus 4.7, which is absolute state-of-the-art for coding. But here’s the problem…. It’s a Guardrail Failure. While it’s cool that I can get data structures with my Big Mac, this is a major "UX Logic Leak." From a product perspective, your AI shouldn't be a polymath - it should be a specialist. Have you seen other examples of AI agents doing the unexpected? #AIAgents #UXDesign #UserTestingLab #Maccas #AIUX