Python Movie Recommendation System with Scikit-learn and Streamlit

Sharing Part 2 of my final year project, where I focus on building the dashboard layer of the system using Python. In this video, I explain how the dashboard code is structured to visualize and present the model outputs in a clear and user-friendly way. This step bridges the gap between machine learning models and real-world usability. 🔹 Dashboard logic and structure 🔹 Integration with trained ML models 🔹 Preparing outputs for visualization 🔹 Designing a clear flow for end-user interaction 📌 Results and performance analysis will be shared in the next video, where I’ll walk through the outputs and insights generated from the models. This phase helped me understand the importance of data visualization, interpretability, and application-oriented ML development. Looking forward to sharing the results soon! Feedback and suggestions are always welcome 😊 #FinalYearProject #Python #DashboardDevelopment #MachineLearning #DataVisualization #DataScience #StudentDeveloper #LearningInPublic

🔥 𝐉𝐮𝐬𝐭 𝐩𝐮𝐛𝐥𝐢𝐬𝐡𝐞𝐝 𝐨𝐧 𝐌𝐞𝐝𝐢𝐮𝐦! 🚀 Hybrid Search RAG That Actually Works — a practical guide to building better RAG systems with BM25 + Vector Search + Reranking in Python. If you’ve struggled with “dumb RAG” — wrong answers, hallucinations, fuzzy retrieval — this article shows how to make RAG accurate, reliable, and production-ready. 💡 👉 Learn how combining keyword precision (BM25), semantic power (vector embeddings), and reranking accuracy can transform your retrieval pipeline. 𝐑𝐞𝐚𝐝 𝐡𝐞𝐫𝐞: https://lnkd.in/genyQX44 #RetrievalAugmentedGeneration #AI #MachineLearning #Python #MLOps

🚢 Titanic Survival Prediction – Machine Learning & Streamlit ✅ Developed and deployed a user-friendly Streamlit web application to predict Titanic survival using Machine Learning, with clear model comparison and performance insights GITHUB LINK : https://lnkd.in/gaptG8kv STREAMLIT.IO LINK : https://lnkd.in/g6R6TwAd #DataScience #MachineLearning #Streamlit #Python #MLProject #LearningJourney #CareerRestart

🪙 Gold Price Prediction using Machine Learning Built a Streamlit web app that predicts gold prices using a Linear Regression model trained on real historical data. 🔧 Tech : Python, Pandas, scikit-learn, Streamlit 🔹 Trained a Linear Regression model on historical gold price data 🔹 Used features like SPX index, Oil price, Silver price, and EUR/USD 🔹 Developed an interactive Streamlit web app for real-time user input Learning by building 🚀 #MachineLearning #Python #Streamlit #DataScience #LearningJourney #Projects

🐍 Python & AI: The Perfect Duo! Just realized how powerful Python is when combined with AI/ML frameworks. Whether you're working with: ✨ LLMs using LangChain or Llama Index ✨ Computer Vision with OpenCV & PyTorch ✨ Building automation bots with Python ✨ Data processing with Pandas & NumPy Python remains the go-to language for AI development. The simplicity of syntax paired with powerful libraries makes rapid prototyping and deployment a breeze. Currently exploring Django REST APIs for AI-powered applications. The possibilities are endless! 🚀 What's your favorite Python library for AI? Let me know in the comments! #Python #AI #MachineLearning #Django #Automation #TechLearning

⌛ This was 8 years ago, and if you try Python in Excel it feels like a feature they are still "considering." The real way to integrate Python and Excel is to move your Excel work to Python environments -- NOT jam python functions into your workbook. Python environments can handle larger datasets, faster processing, and more sophisticated AI. This is what we are building at Mito AI. The Excel-user front end for Python/AI workflows 🚀 #AI #Excel #Python #Data #DataScience

Every Tuesday and Thursday, I send 2 tips to help you discover useful Python tools for data and AI. Recent tips: • PydanticAI: Type-safe LLM outputs with auto-validation • Polars: Stream million-row exports without memory spikes • Narwhals: One function for pandas, Polars, and DuckDB • uv: Switch Python versions without rebuilding environments It's free on Substack. 📬 Subscribe here: https://bit.ly/46fdOPl #Python #DataEngineering #AI #OpenSource #PythonTips

Vector databases are quickly becoming the backbone of modern AI systems — from semantic search to production-grade RAG pipelines. In this Medium article, I break down how FAISS, Chroma, and Pinecone work in Python, where each one fits best, and how to choose the right tool for real-world AI applications. If you’re building LLM-powered products or scalable search systems, this is a practical, developer-focused read worth your time. #VectorDatabases #Python #ArtificialIntelligence #MachineLearning #LLM #RAG #SemanticSearch #FAISS #ChromaDB #Pinecone #AIEngineering

What I learned from 𝗩𝗮𝗻𝗶𝘀𝗵𝗶𝗻𝗴 𝗚𝗿𝗮𝗱𝗶𝗲𝗻𝘁𝘀 Today 🎙️ 𝗣𝗼𝗱𝗰𝗮𝘀𝘁: Vanishing Gradients with Hugo Bowne-Anderson 𝗘𝗽𝗶𝘀𝗼𝗱𝗲: Python is Dead. Long Live Python! With the Creators of pandas & Parquet 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆 When AI writes code, the slowest part is not typing. It is running tests. The faster your tests run, the faster AI can build and fix code. Having different AI models review the same code catches more mistakes. One model writes code. Other models check it. This finds bugs that humans would miss. 𝗪𝗵𝘆 𝗜𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 This changes which tools we pick. If AI does the coding, we want tools that run fast, not just tools that are easy to write. Speed matters more than comfort now. 𝗥𝗲𝗳𝗹𝗲𝗰𝘁𝗶𝗼𝗻 🧠 This made me think differently about choosing tools. I used to pick what was easy for me to write. Now I see that when AI writes code, what matters is how fast it runs and tests. The way we work is changing. To get the full insight, check out the podcast! #VanishingGradients #DataScience #Python #AI #MachineLearning #SoftwareEngineering #AgenticDevelopment #DataEngineering #TechCareers #FinancialAnalysis #PowerBI #SQL #ArtificialIntelligence #FutureOfWork #TechRecruitment

Google Colab should have a variable inspector with easy-to-access statistics for collections, such as unique, maximum, minimum, and shape. I don't have to open a cell type the name of the variable to know its current type, shape, and value. Frictionless. #MachineLearning #DataScience #GoogleColab #DeveloperExperience #AIWorkflow #Productivity #Python #DeepLearning