Pinned Repositories
IPL_Match_Winner_Prediction
The IPL Win Predictor is a Streamlit web app that forecasts the probability of a cricket team winning an IPL match. Users input match details, and the app calculates key metrics to provide win probabilities for both teams based on historical data. Enjoy predicting outcomes! The model accuracy comes out to be 80%.
Emotion_Detection_Python
This repository features a deep learning model for real-time emotion detection from facial expressions using a webcam. Built with Keras and TensorFlow, it classifies emotions such as anger, disgust, fear, happiness, neutrality, sadness, and surprise. This leverages Haar Classifier for face detection and processes images for optimal performance.
js-react-project
Libas_traditionals
Libas (Cloths & Attire) is an online store offering traditional Kurta Hizar for men, Ridas for women, and children's clothing. We provide high-quality, culturally appropriate clothing for the Dawoodi Bohra community, combining tradition with modern design. Shop at Libas for modest, elegant attire for all occasions.
Murtaza-mahudawala
Config files for my GitHub profile.
Python_ML-
Sentiment_Analysis
shoe-website
Spam_Email_Detection
This project focuses on detecting spam emails using machine learning techniques. Various preprocessing steps, exploratory data analysis (EDA), and machine learning models were used to classify emails as spam or non-spam. The final model utilizes a VotingClassifier for optimal performance by combining the strengths of multiple algorithms.
Topic_Classification_SLM
This repository contains a PyTorch-based text classification model for the AG News dataset. The model uses embeddings and a fully connected layer for classification. Tokenization is done via NLTK, and the model is optimized using Adam. After 10 epochs, the model achieved a test accuracy of 91.45%.
Murtaza-mahudawala's Repositories
Murtaza-mahudawala/Spam_Email_Detection
This project focuses on detecting spam emails using machine learning techniques. Various preprocessing steps, exploratory data analysis (EDA), and machine learning models were used to classify emails as spam or non-spam. The final model utilizes a VotingClassifier for optimal performance by combining the strengths of multiple algorithms.
Murtaza-mahudawala/Emotion_Detection_Python
This repository features a deep learning model for real-time emotion detection from facial expressions using a webcam. Built with Keras and TensorFlow, it classifies emotions such as anger, disgust, fear, happiness, neutrality, sadness, and surprise. This leverages Haar Classifier for face detection and processes images for optimal performance.
Murtaza-mahudawala/IPL_Match_Winner_Prediction
The IPL Win Predictor is a Streamlit web app that forecasts the probability of a cricket team winning an IPL match. Users input match details, and the app calculates key metrics to provide win probabilities for both teams based on historical data. Enjoy predicting outcomes! The model accuracy comes out to be 80%.
Murtaza-mahudawala/Topic_Classification_SLM
This repository contains a PyTorch-based text classification model for the AG News dataset. The model uses embeddings and a fully connected layer for classification. Tokenization is done via NLTK, and the model is optimized using Adam. After 10 epochs, the model achieved a test accuracy of 91.45%.
Murtaza-mahudawala/Sentiment_Analysis
Murtaza-mahudawala/Libas_traditionals
Libas (Cloths & Attire) is an online store offering traditional Kurta Hizar for men, Ridas for women, and children's clothing. We provide high-quality, culturally appropriate clothing for the Dawoodi Bohra community, combining tradition with modern design. Shop at Libas for modest, elegant attire for all occasions.
Murtaza-mahudawala/Python_ML-
Murtaza-mahudawala/Murtaza-mahudawala
Config files for my GitHub profile.
Murtaza-mahudawala/js-react-project
Murtaza-mahudawala/shoe-website