The "House Price Prediction" project focuses on predicting housing prices using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, and XGBoost, this project provides an end-to-end solution for accurate price estimation.
Release packages of Kemet, a guarded gateway between coding agents and sensitive databases. Assets only; no source.
The "Rock vs. Mine Prediction" project focuses on predicting whether an underwater object is a rock or a mine using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), and logistic regression, this project provides an end-to-end solution for accurate classification.
The "Heart Disease Prediction" project focuses on predicting the presence of heart disease in individuals using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, and Scikit-learn (sklearn), this project provides a comprehensive solution for accurate disease prediction.
The "Gold Price Prediction" project focuses on predicting the prices of gold using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, Random Forest Regressor, and others, this project provides a comprehensive solution for accurate price estimation.
This project is a simple license plate detection system implemented in Python using OpenCV, EasyOCR, and Matplotlib libraries.
The "Breast Cancer Classification using Neural Networks" project focuses on predicting the presence of breast cancer using deep learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and implementing neural networks.
Welcome to BrainBoost, our e-learning website prototype! BrainBoost is the ultimate destination for learning in-demand tech skills.
This project focuses on predicting the approval or rejection of loan applications using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), and Seaborn, this project provides an end-to-end solution for loan status prediction.
This is a repo that contains introductory topics in machine learning, very summarised.
This project focuses on detecting cars in traffic images using Python, OpenCV, NumPy, and other libraries. The implementation is done in Google Colab, making it accessible and easy to run for anyone interested in understanding or utilizing the code.
Machine Learning Powered Stock Market Trading Bot
This project aims to detect cars in traffic images using PyTorch, matplotlib, NumPy, and OpenCV (cv2). The detection model is implemented using a deep learning approach and trained on a dataset of traffic images.
The "Car Price Prediction" project focuses on predicting the prices of cars using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, Lasso regression, and Linear regression, this project provides a comprehensive solution for accurate price estimation.
The "Diabetes Prediction" project focuses on predicting the likelihood of an individual having diabetes using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), and Support Vector Machines (SVM), this project offers a comprehensive solution for accurate classification.