{"repo":"ArshiBansal/Stocks_Analysis","free":true,"listed":false,"github":"https://github.com/ArshiBansal/Stocks_Analysis","clone":"git clone https://github.com/ArshiBansal/Stocks_Analysis.git","description":"Comprehensive stock market analysis for major tech companies (2019–2024). Features data cleaning, feature engineering, classical time series (SARIMA & Prophet), supervised & unsupervised ML, and neural networks. Available as both a Jupyter notebook for experimentation and a Streamlit app for interactive exploration.","language":"Python","stars":23,"topics":["data-analysis","data-science","data-visualization","framework","jupyter-notebook","python","python3","pythonframework"],"license":"MIT","category":"analytics","readme_excerpt":"Magnificent 7+ AI Stock Forecasting System A forecasting pipeline daring enough to face live markets — and lose with dignity. One repository. One slightly delusional idea. Two execution personalities: naïve hope and cold, hard Python. Static Kaggle data for research. Live yfinance data for public embarrassment. Watch the models duke it out with reality → Streamlit App No login. No magic screenshots. Just live prices, live chaos, and zero excuses. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Most projects stop at pretty charts . Most notebooks stop at impressive metrics . But very few dare to ask the real questions: Which model survives sudden market tantrums? Which one folds under volatility like my first attempt at coding? Which model looks perfect until live data reality crashes the party? This project exists to answer those questions — outside cozy notebooks , in the unforgiving market arena , with zero excuses . • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • The Magnificent 7+ AI Stock Forecasting System is a dual-mode forecasting pipeline designed to answer one uncomfortable question: What actually survives when models leave notebooks and face live markets? It seamlessly combines offline experimentation with live forecasting, allowing model performance to be evaluated under real volatility , real noise , and real consequences . No curve-fitting theatrics. No cherry-picked screenshots. Just models, ma","default_branch":null,"files":null,"tree":[],"storefront":"/r/ArshiBansal","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ArshiBansal/Stocks_Analysis/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}