An analysis on Iris dataset of Scikit learn

Data analysis with Python to building and evaluating data models

This repository contains my AVETTI Commerce internship's reports and predicting accuracy of the models.

Github repo for my in-progress book, "Visualizing Multivariate Data and Models in R"

Implementations of main Machine Learning Agorithms from scratch: Gaussian Mixture Model, Gradient Boosting, Adam, RMSProp, PCA, QR, Eigendecomposition, Decision Trees etc.

Content from the AI laboratory

🌊The project analyzes water consumption trends in Catalonia using government-provided open data. After data collection via API proceeds with EDA to uncover patterns. Feature Engineering enhancing, followed by preprocessing for Linear Regression. The core focus lies in building regression model to predict water usage, with result analysis.🌧️

This repo contains various Regression Models

Introduction to Python and Neural Network with Keras and PyTorch for beginners

visual (inertia) odometry of a drone with a monocular camera

Crypto Forecast Backend is a Flask-based API service designed to provide cryptocurrency price predictions based on historical data. Leveraging machine learning algorithms, it analyzes past price trends and generates forecasts for various cryptocurrencies.

Simple Model which predicts house price taking based on Size and number of bedrooms , my first project in mechine learning and dealing with datasets learnt by prompting and developped using jupyter lab , notebook in 1.5 hours with so little dataset of 100 records that to generated by gpt 3.5 , soon train and test with more data ...

This repository contains the Plant Ecosystem Analysis project, utilizing R to investigate the relationship between native plant species richness and ecological factors within diverse geographical gradients.

This project employs multiple regression analysis to identify key determinants of employee salaries, such as experience and education, using R. Through extensive data analysis and model comparisons between Linear Regression and Random Forest, the study offers insights for effective salary structuring and employee retention strategies.

This library gives a modular design for better control of gradient passing between architecture components. Useful for architectures not using a traditional forward and backward pass.

Implementation of common machine learning models using only numpy and pandas.

A simple implementation of the LOESS algorithm using numpy

This project explores the applicability of various machine learning models to predict whether a crime was solved, based on a comprehensive dataset from the USA for the period 1980-2014.