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Predicting TTC delays for a smoother, more reliable commute.
Finding affordable housing in Toronto is tough. So, we created the T-PPP web app (an ML based model) to forecast housing prices based on key property features to help out.
Age & Gender Prediction from X-Rays: Enhancing Healthcare Diagnostics with AI.
AI-Powered Fake News Detector – Verify News Authenticity Instantly!
Detect and prevent with DDosTection
This Crop Disease Detection App helps farmers and gardeners detect diseases in their plants instantly.
NeuroDetect: "Spot Tumors Early, Act with Confidence."
Exposing Deepfakes with AI: Securing Digital Truth.
Understanding Postpartum Depression Through Data-Driven Insights
People Counting System with OpenCV, Python, and YOLO
My project aims to develop an advanced mobile security application using AI&ML technologies to protect mobile from cyber threats(blackmail calls, suspicious emails, app hacking and camera access)
An AI-powered App for Forecasting Home Prices
Our AI system uses two CNN models—Continuum (optical) and Magnetogram (magnetic)—to forecast space weather. Using API data, it predicts risks early, triggering satellite panels to close during threats
After analyzing Canada's tech startup landscape, we built VCDash - a canvas tool where VCs can freely arrange charts, connect insights, and communicate discoveries in one intuitive space.
My Analysis
This report analyzes trends in Canadian tech investments, highlighting key sectors, growth drivers, and future prospects, offering actionable insights for investors navigating the evolving landscape.
Dive into Canada's tech gold rush with Maple Valley!
A model that predicts the 5-day return and price of selected stocks using an ensemble of CatBoost, LightGBM, and a Neural Network.
Next-event predictive modelling and user journey map.
We provide a model to predict the value of five stock tickers using a Random Forest Regressor model and a LSTM model.
Optimizing User Engagement on the Federato RiskOps Platform: A Data-Driven Approach
Forkast leverages machine learning to predict future order volumes based on your inputs, helping you generate accurate forecasts that streamline operations, optimize resources, and drive success
We blend predictive models—XGBoost, LSTM, and SVR—then fine-tune their outputs with a Gradient Boosting layer. Using technical, options, and sentiment data, we aim for smarter stock forecasts.
