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Model-Evaluation-with-Cross-Validation

Utilizing k-fold cross-validation, this section evaluates the accuracy of Logistic Regression, Random Forest Classifier, and Support Vector Machine (SVM) models on the MNIST dataset, aiding in understanding their performance for digit recognition tasks.

RandomForest-Digit-Classifier

Implementation of Random Forest classifier for digit recognition using scikit-learn. Trained on the MNIST dataset, the model predicts the digit represented by images based on pixel values. Includes training, testing, and evaluation of the classifier.

DecisonTreeClassifier-Titanic-Survival-prediction

Predicting survival on the Titanic using Decision Tree Classifier: Explore a predictive model trained on Titanic passenger data to determine survival outcomes, employing Decision Tree Classifier for classification tasks

SupportVectorMachine-Iris-Classifier

Implementation of Support Vector Machine (SVM) for Iris flower classification using scikit-learn. Trained SVM model predicts iris species based on features such as sepal length, sepal width, petal length, and petal width.

LogisticRegression-BinaryClassification

Implementing logistic regression in Python with Scikit-learn, this Jupyter Notebook predicts customer churn based on salary and other factors, aiding in proactive retention strategies.

LogisticRegression-Multiclass-Classification

This repository contains Python code for a logistic regression model trained on the digits dataset from scikit-learn. The model is trained to recognize handwritten digits. It includes data preprocessing steps, model training, and prediction.

littlelemon

A mini django project. Food ordering website

netflix-clone

Todo-Django

personal-portfolio

LibraryManagementSystem

Mini Python Project

MachineLearning-TrainData-TestData-Split-Program

This repository hosts a program designed to facilitate the splitting of datasets into training and testing subsets for machine learning tasks. The program ensuring that the data is appropriately divided into separate sets for training and evaluating the performance of machine learning models.

ResaleValuePrediction-Using-Dummy-Variables-Linear-Regression

This repository contains code for predicting the resale value of vehicles using linear regression with dummy variables. The project focuses on leveraging dummy variables to represent categorical features in the dataset and applying linear regression to predict the resale value of vehicles based on various factors such as mileage and age

TextAutocomplete-LSTM-Tensorflow

Text Autocomplete with TensorFlow LSTM is a project that demonstrates how to build a simple text autocomplete system using TensorFlow and LSTM (Long Short-Term Memory) networks. This project utilizes a dataset of frequently asked questions (FAQs) to train the LSTM model to predict the next word given a sequence of words.

Gradient-Descent-Algorithm-Implementation

This repository contains Jupyter Notebook files implementing the Gradient Descent algorithm from scratch. The notebook demonstrates the step-by-step implementation of Gradient Descent for finding the slope and intercept of a linear regression model.

MachineLearningModelSaving

This repository provides simple yet comprehensive examples and tutorials for saving machine learning models using two popular serialization libraries: pickle and joblib. Learn how to persist trained models with ease, ensuring seamless deployment and sharing across different environments.

salary-prediction

The repository 'salary-prediction' contains code implementing a multivariate linear regression model for predicting salaries. The model utilizes features such as years of experience, test scores, and interview scores to estimate a candidate's salary.

capital-income-prediction-canada

Predicting capital income of Canada using linear regression in a Jupyter notebook. This project explores the relationship between various factors and capital income in Canada, employing linear regression techniques for prediction.

TextAutocomplete-HuggingFace

This repository demonstrates how to use the HuggingFace Transformers library to implement text autocompletion in a Jupyter Notebook environment.

TextAutocomplete-distilgpt2

This repository contains the code and resources for implementing text autocompletion using the DistilGPT-2 model from Hugging Face within a Jupyter Notebook environment.

TextAutocomplete-LSTM-pytorch

This repository contains a Jupyter Notebook demonstrating text autocompletion using Long Short-Term Memory (LSTM) networks implemented in PyTorch.

Gemini-LangChain-Chatbot

Gemini LangChain Chatbot is a Streamlit web application that allows users to have conversations with a language model powered by Google's Generative Gemini AI API and LangChain. This chatbot is designed to provide engaging and creative responses to user inputs.

Gemini-LangChain-MultiPDF-Chatbot

Gemini-Powered-MultiPDF-Chatbot is a Streamlit application that leverages Google Generative AI Gemini and LangChain for conversational question-answering based on PDF documents. This chatbot allows users to ask questions related to the content of uploaded PDF files.

Youtube-Transcription-Whisper

This jupyter notebook project empowers you to seamlessly download YouTube videos, extract their audio tracks, and transcribe the speech content using OpenAI's powerful Whisper model.

MultilingualText-to-Image-Generation

This project demonstrates the generation of images based on textual prompts using a stable diffusion model. The text prompts are translated into multiple languages using Google Translate before generating images.

Image-to-Text-Generation

This repository contains a Jupyter Notebook that demonstrates how to use a pre-trained Vision Encoder-Decoder model for image captioning.

Text-to-Image-Generation

This project demonstrates how to generate images using diffusion models, specifically utilizing the Stable Diffusion model from Hugging Face's Transformers library.

ElasticNet-MLflow-Regression

This repository contains code for training an ElasticNet regression model using MLflow. The model predicts the quality of wine based on various features.

Vehicle-Tracking-Counting-YOLOv8

This Jupyter notebook project uses YOLOv8 for vehicle tracking and implements a line crossing detection algorithm. The system counts vehicles that cross a specified line in a video, annotates the frames, and generates an output video with visualizations.

3D-Surface-Prediction-Tensorflow

This project demonstrates the creation of a 3D surface prediction model using TensorFlow. The model is trained on a randomly generated dataset and visualizes the predicted surface in a 3D space.