This is a simple machine learning project using classifiers for predicting factors which affect student grades, using data from CSV file

🤗 Push your spaCy pipelines to the Hugging Face Hub

A collection of handy ML and data visualization and validation tools. Go ahead and train, evaluate and validate your ML models and data with minimal effort.

This project demonstrates the application of machine learning techniques to predict house prices based on various features. By analyzing the dataset, preprocessing the data, and selecting an appropriate model, we were able to achieve a high level of accuracy in predicting house prices. The trained model can be further refined and deployed.

Prinz provides ML integrations for Nussknacker.

Experience a comprehensive exploration of Spotify's musical landscape seamlessly transitioned from Tableau visualizations to SQL analysis. Dive into track inventory, streaming metrics, and sonic trends via interactive dashboards, while leveraging SQL queries for deeper insights into KPIs and cross-platform rankings.

Pre-trained image models using ONNX for fast, out-of-the-box inference.

Part of the Hydrosphere.io project.

Awesome papers on Machine Learning and Statistical Models

Customer Segmentation using Clustering (Machine Learning)

Handwriting Detection using Deep Learing with Neural Network, tensorflow, keras and jupyter notebook

This dataset is used to detect the credit card fraud detection. This is a classification problem. This is an imbalanced dataset based on target variable. So In this Project, I will use encoding and decoding techniques to balanced dataset.

A Regression based ML model for prediction of car prices in market

Beautiful Web interface made using Streamlit for quick Exploratory Data Analysis and building classification models which are implemented from scratch.

Titanic Survival Prediction using Logistic Regression

Developed an Amazon laptop price prediction tool using machine learning algorithms, integrated with a Streamlit app for an interactive user experience.

Predict diseases with the help of AI to save cost, time, and to prevent misdiagnosis.

Using Various ML/DL models to detect the fake news.

Machine Learning Project

This project aims to develop a predictive model estimating insurance coverage costs for customers based on their attributes and product choices. The dataset includes transaction and quote details for policy purchasers. The objective is to predict quoted coverage costs, considering customer traits and 7 customizable product options.