modeltraining

There are 40 repositories under modeltraining topic.

  • Realtime-Sign-Language-Detection-Using-LSTM-Model

    AvishakeAdhikary/Realtime-Sign-Language-Detection-Using-LSTM-Model

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

    Language:Jupyter Notebook24226
  • itsmethahseer/classfication_part2

    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.

    Language:Jupyter Notebook5100
  • SilenceGeneric/DarkAI

    A dark web analysis tool.

    Language:Python2200
  • SURESHBEEKHANI/Finetune-LLAMA-2-On-Your-DataSet-AutoTrain-From-Hugging-Face

    This project fine-tunes the LLaMA-3.1-8B model using LoRA adapters for parameter-efficient training. It leverages chat templates for conversation structuring, utilizes 4-bit quantization for memory efficiency, and saves the fine-tuned model for deployment on the Hugging Face Hub.

    Language:Jupyter Notebook20
  • bilet-13/No_code_DNN

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

    Language:Python1100
  • Jimmymugendi/Titanic-Survival-Prediction-Using-Machine-Learning

    An advanced machine learning project deploying a model for Titanic passenger survival prediction, including deployment on ngrok for easy access.

    Language:Jupyter Notebook110
  • rishaviitd/Piramal_hackathon

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

    Language:Jupyter Notebook1100
  • samchak18/Capstone_Project_3_Coronavirus-Tweet-Sentiment-Analysis

    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.

    Language:Jupyter Notebook1101
  • ShivangeeRajput/AgroShield

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

    Language:Java1100
  • Kaggle-Challenge-Team-17

    7PAM2015-0105-2023-TEAM17/Kaggle-Challenge-Team-17

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

    Language:Jupyter Notebook0000
  • Anithanaidu33/Stock-Prediction

    This project aims to predict the future stock prices of various companies using machine learning and deep learning techniques. By analyzing historical stock price data and incorporating relevant features, the goal is to build accurate and robust models that can forecast stock prices over different time horizons.

  • Anithanaidu33/Titanic-Classification

    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.

    Language:Python0100
  • khizraayaseen/AI-price-prediction

    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.

    Language:Jupyter Notebook0100
  • Mahenoor-Merchant/Diabetes-Prediction

    The Diabetes Prediction Model is a machine learning application that predicts diabetes based on input features such as pregnancies, glucose level, blood pressure, skin thickness, insulin, BMI, diabetes pedigree function, and age. It utilizes a logistic regression algorithm for binary classification.

    Language:Jupyter Notebook00
  • nardyjh/deep-learning-model

    Alphabet Soup Charity: A deep learning model to predict the success of charitable donations, enhancing decision-making for fund allocation and impact optimization.

    Language:Jupyter Notebook0100
  • OmerGamie/mlproject

    This repo hosts an end-to-end machine learning project designed to cover the full lifecycle of a data science initiative. The project encompasses a comprehensive approach including data Ingestion, preprocessing, exploratory data analysis (EDA), feature engineering, model training and evaluation, hyperparameter tuning, and cloud deployment.

    Language:Jupyter Notebook0100
  • rachitdani/Credit-Card-Fault-Detection-Project

    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

    Language:Jupyter Notebook0100
  • shubhamparmar1/FraudShield

    This project aims to develop a machine learning model for proactive fraud detection in financial transactions.

    Language:Jupyter Notebook00
  • shubhamparmar1/Gold-en-Eye

    This project aims to develop a forecasting model for predicting the price of gold.

    Language:Jupyter Notebook0100
  • shubhro2002/Life-Expectancy-Analysis-and-Prediction

    This repository contains the LifeExpectancy Prediction Project, a comprehensive data science project aimed at predicting life expectancy based on various health, economic, and social factors. The project includes steps for data preprocessing, exploratory data analysis (EDA), model selection, training, hyperparameter tuning, and model interpretation

    Language:Jupyter Notebook0101
  • SililaWijesinghe/Vegetable-Detection-with-Tensorflow-learning-PYTHON

    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.

    Language:Jupyter Notebook0100
  • ainy-rehman/largelanguagemodel_consumerbrand

    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.

    Language:Jupyter Notebook10
  • arjunraj79/Custom_NIDS_with_ML

    A simple Python script to check the strength of a password based on length, the inclusion of numbers, special characters, and upper/lower case letters.

    Language:Python10
  • bizzorotical-ank01/Diabetes-Prediction-System

    Diabetes Prediction Web App

    Language:HTML10
  • Chatura-17/Car-Price-Prediction

    This project aims to predict the prices of cars based on various features such as year of manufacture, brand, mileage, and other relevant factors. Leveraging machine learning algorithms, this project explores different regression techniques to create an accurate model for car price prediction.

    Language:Jupyter Notebook
  • dheerajkallakuri/Posture-Prediction-with-Neural-Networks

    Posture classification system that uses an IMU sensor.

    Language:C++
  • ghulam-ahmad-1/House-prize-Prediction

    Model Trainig To predict the Prize Of House

    Language:Jupyter Notebook10
  • Huzaifa-367/MLOps-Text-Classification

    Text Classification with Naive Bayes

    Language:Jupyter Notebook10
  • Jatin-Mehra119/Heart_Disease_Predictor

    Data Analysis, Model Training, Model Deployment.

    Language:Jupyter Notebook10
  • PartiGayatri/heart-failure-prediction

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

    Language:Jupyter Notebook
  • SemesterProjectSixth/Text-Summarizer

    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.

    Language:CSS
  • shubhamdeepkeshav/FRAUD-DETECTION-PROJECT

    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.

    Language:Jupyter Notebook10
  • shubhamsoni98/Capstone_Project_1_Financial-Analytics

    Predicting Stock Prices for Top 5 Global Tech Companies

    Language:Jupyter Notebook
  • shubhamsoni98/Classification-with-Random-Forest---2

    Fraud detection is a critical task for financial institutions and businesses. This document outlines the end-to-end process of predicting fraudulent activities using a Random Forest model. The process includes data preparation, exploration, model training, and evaluation.

    Language:Jupyter Notebook
  • shubvats/house-price-prediction

    Repository for predicting house prices using the Ames Housing dataset. Implements advanced regression techniques with TensorFlow Decision Forests, including Random Forests. The project covers data exploration, feature engineering, model training, evaluation, and visualization.

    Language:Python20
  • Thilagavijayan/Datascience_Mentorship_and_Development

    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

    Language:Jupyter Notebook10