House Price Predictor 🏡 "A machine learning model that predicts house prices based on square footage, number of bedrooms, and bathrooms using Linear Regression. The project includes data preprocessing, model evaluation, and visualization of actual vs. predicted prices."

A robust image classifier using CNNs to efficiently classify different plant seedlings and weeds to improve crop yields and minimize the extensive human effort to do this manually.

Scientific programming through the SKLearn / Scikitlearn library

`Spltr` is a simple PyTorch-based data loader and splitter. It may be used to load arrays and matrices or Pandas DataFrames and CSV files containing numerical data with subsequent split it into train, test (validation) subsets in the form of PyTorch DataLoader objects.

1. train_test_split 2.K_fold 3.LeaveoneOut 4.Cross Validation Score 5.Logistic Regression

Project code for AI Programming with Python Nano-degree Program

This program predicts stock patterns labels and classes based on available stock data. Years 1, 2, and 3 are training years and 4 and 5 are testing. This program also uses ensemble learning, W as a hyperparameter, and an oracle.

A deep learning model employing linear regression to uncover intricate patterns and relationships within data, enabling accurate predictions and precise estimation. Harnessing the power of neural networks, it maximizes the potential of linear regression for enhanced performance and advanced modeling.

A project showcasing the various steps involved in carrying out a basic linear regression task for prediction of a target variable.