This project is intended on precision farming to build predictive model so as to suggest the most suitable crops to grow based on available climatic & soil.

Machine Learning Clustering Techniques for Customer Segmentation - Certification Project

K-Means Clustering for the coping strategies of Brief COPE Questionnaire

Customer Segmentation using K-Means clusters customers based on spending habits, age, and income. This helps target marketing strategies, improve customer understanding, and maximize profits through tailored approaches.

K-means algorithm visualizer with c

Applying clustering algorithms like Latent Dirichlet Allocation (LDA) and K-means to group similar documents together for topic modeling and understanding large text corpora.

K-means clustering algorithm using MapReduce.

In this machine learning project, we will make use of K-means clustering which is the essential algorithm for clustering unlabeled dataset.

In this project, we focused on a television studio and the decision-making process for producing our next TV show. We conducted a market analysis to understand the content offerings on mainstream platforms like Netflix, Hulu, and Amazon Prime Video, and explored potential market opportunities.

This project aims to cluster various cryptocurrencies based on their market performance using machine learning techniques. The analysis involves several key steps: normalizing the data, reducing its dimensionality with Principal Component Analysis (PCA), and using K-Means clustering to identify distinct groups.

This repository contains customer segmentation project which I have implemented so far. Other segmentation projects will be showcased here.

Workspace for applied problems of probability theory & mathematical statistics class

This repository contains functions/codes related to different methods of machine learning for classification and clustering in python.

LOFAR System Health Management

Customer segmentation in the airline industry for targeted marketing and growth opportunities

Este proyecto es un prototipo de aplicación en C++ con interfaz Qt. Aplica transformaciones, muestra información relevante y opera filtros en el Bitmap para comprender los fundamentos de Visión por Computadora y Procesamiento Dígital de Imágenes.

All my learnings from "Machine Learning with Python" course offered by "IBM" on Coursera are reflected here.

Built a model to create highlights/summary of given video. The results of this study shows that, with a remarkable similarity index(SSIM) of 98%, the recommended technique is quite successful in choosing keyframes that are both educational and distinctive from the original movie

Impementaion of various AI models using Numpy