a library so simple you will learn Within An Hour
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Updated
Nov 19, 2025 - Python
a library so simple you will learn Within An Hour
End-to-end visual speech recognition system using deep learning. Combines computer vision and NLP to transcribe spoken words from lip movements in video sequences.
This project, you will build a full AI pipeline for an image classification task using Convolutional Neural Networks (CNNs). The project will cover data ingestion, preprocessing, model training, deployment, and CI/CD integration using GitHub Actions, Docker, and AWS.
This project analyzes IMDb movie reviews to classify sentiments as positive or negative. It includes text preprocessing, feature extraction using TF-IDF and CountVectorizer, training Logistic Regression and Naive Bayes classifiers, and visualizing frequent words with WordClouds.
This project aims to build a machine learning pipeline that predicts customer churn using AWS services like SageMaker for model training and deployment, along with Docker for containerization.
A real-time, end-to-end machine learning application built with Flask and integrated with MLflow for tracking and model management. The application predicts house prices based on user input, leveraging trained regression models and providing a web interface for seamless interaction.
In this project, I've created an end-to-end ETL pipeline and subsequently developed a machine learning model to predict the price of Amazon products based on several product-related features.
A Python implementation of multiple linear regression to predict the profit of startups based on their spending in R&D, Administration, Marketing, and the state they operate in.
Code that can be used for training a neural network model to classify input documents into distinct classes.
Code that can be used for training a neural network model to detect faults (sticky notes, folded corners etc.) in input documents.
This project implements **Random Forest Regression** to predict the salary of an employee based on their position level. Using a dataset that includes position levels and corresponding salaries, this project demonstrates how an ensemble method like Random Forest can improve prediction accuracy by averaging multiple decision trees.
An Image classifier model and builder for binary image classification.
This project is an end-to-end MLOps pipeline for a network security system that detects phishing and malicious activities using machine learning. It automates data ingestion, preprocessing, model training, and deployment while leveraging AWS S3 for model storage and GitHub Actions for CI/CD. The system includes realtime monitoring & a web interface
Tire condition classification using ResNet and transfer learning. This project applies deep learning to identify whether a tire is in good or bad condition based on image data.
implementation of novel Segformer neural network variants dubbed "LRSegformer" which includes Lipschitz-regularized MLP decoder layers to improve training stability and prevent overfitting
Food delivery time prediction
This project provides a comprehensive guide to implementing PCA from scratch and validating it using scikit-learn's implementation. The visualizations help in understanding the data's variance and the effectiveness of dimensionality reduction.
ML Project: Students-Grade Public
A deep learning model that classifies traffic signs using the German Traffic Sign dataset to assist autonomous vehicles in recognizing road signs.
Comment classifier model trainer using keras tensorflow, stanza tokenizer and transformers.
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