Realtime Sign Language Detection: Deep learning model for accurate, real-time recognition of sign language gestures using Python and TensorFlow.

Welcome to the Machine Learning Repository! This repository is a collection of notebooks showcasing various machine learning projects and implementations. It incluedes Decision tree algorithm, Random forest , Support vector machine etc.

A dark web analysis tool.

AlmaBetter Capstone Project -Classification model to predict the sentiment of COVID-19 tweets. The tweets have been pulled from Twitter and manual tagging has been done then.

A Deep Learning application designed to detect plant 🌱diseases using images of plant leaves🌿, powered by TensorFlow technology.

Machine Learning model capable of accurately predicting the Rate of Interest (ROI) from bureau data

Web platform allows users to upload CSV files and train a machine learning model using the uploaded data

The Titanic classification problem involves predicting whether a passenger on the Titanic survived or not, based on various features available about each passenger. The sinking of the Titanic in 1912 is one of the most infamous maritime disasters in history, and this dataset has been widely used as a benchmark for predictive modeling.

This repository serves as a comprehensive resource for understanding and implementing various feature selection techniques, gaining familiarity with Jupyter Notebook, and mastering the process of model training and evaluation

This project focuses on predicting the prices of clothes based on various features such as category, size, and color. Leveraging the power of machine learning, specifically supervised learning algorithms, we aim to build a robust predictive model capable of estimating prices with high accuracy.

One notebook trains a vegetable classification model with InceptionV3 using TensorFlow and Keras. The second notebook showcases the pre-trained model's inference on vegetable categories, loading InceptionV3 and enhancing image features. Together, they offer a compact solution for vegetable classification through deep learning.

Data Analysis, Model Training, Model Deployment.

Text Classification with Naive Bayes

Welcome to the Fraud Detection Project! This repository uses machine learning 🧠 to detect fraudulent transactions 💳. It includes data preprocessing 🛠️, model training 📚, evaluation 📊, and visualization 📈. Explore, experiment, and contribute 🤝 to improve fraud detection accuracy. Check the README for setup and usage instructions.

This is a Data Science task related to kaggle challenge of Titanic Spaceship

Predicting heart failure using Decision Tree algorithm with a dataset sourced from Kaggle. Achieved 99% accuracy, demonstrating robust performance as a binary classifier.

This project detects if the card holder will default on the credit payment on the following month or not by implementation of various ML Classification Algorithms in a modular coding format

This is a project which allows a user to translate, summarize, paraphrase and humanize it. It is basically a web application that allows user to enhance their content by providing these features.

This project utilizes a machine learning model where consumer brand data is employed. Initially, a preliminary model is developed, followed by a refined model using a process called 'fine-tuning' to improve results. Additionally, a comprehensive testing suite has been created to validate accuracy and reliability of the model's predictions.