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.

Prinz provides ML integrations for Nussknacker.

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.

Part of the Hydrosphere.io project.

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.

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

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

Awesome papers on Machine Learning and Statistical Models

Titanic Survival Prediction using Logistic Regression

Customer Segmentation using Clustering (Machine Learning)

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

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

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.

Machine Learning Project

Machine Learning Project

Machine Learning Project

Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng

Using Scikit-learn and Imbalanced-learn to build and evaluate ML models that predict credit risk