PostgreSQL, docker-compose, classification model, latent semantic analysis, Jupyter Notebook, Wikimedia API

Machine Learning Homework Solution Notebooks (UCF CAP5610)

Repository containing IPython notebooks to Kaggle challenges

This repository is made following the course by Sir Jose Portilla, and focuses on unsupervised Machine Learning algorithms. I studied all these concepts in January 2024

Principle Component Analysis in Python

Sameer Girolkar's AIML practice Notebooks

Notebooks con distintas opciones de recomendadores que voy usando, las ideas principales.

In this project, I will analyze a dataset containing data on various customers' annual spending amounts (reported in monetary units) of diverse product categories for internal structure. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with. Doing so would equip…

In this repository, I am have written notebook on clustering techniques along with hierarchical clustering.

Labs for AI unit using Jupyter notebooks. Topics are deep learning, supervised & unsupervised learning, reinforcement learning.

Análise de Correspondência Simple utilizando dados da compra de Commodities do estado Maharashtra (índia) entre 2014 e 2016 no R Notebook.

Diplodatos 2020

Notebook to run SSL types including autoencoder, denoising autoencoder, parallel autoencoder with embedding loss, and SimCLR. All experiments have simple conv6 backbone.

mobility trends reports (apple maps & google maps)

Machine Learning Internship - Carrer Launcher || Data School. Machine Learning is one of the fastest-growing fields. Repository Contain the Module wise Notebook completed during Internship.

A repository of Jupyter notebooks documenting my learning journey through Andrew Ng's Machine Learning Specialization, showcasing hands-on implementations of machine learning concepts and algorithms.

Can a machine identify a bee as a honey bee or a bumble bee? this notebook walks through building a model that can automatically detect honey bees and bumble bees.

Module 10 - Using python programming and unsupervised learning, I am creating a notebook that clusters cryptocurrencies by their performance in different time periods. Then I will plot the results for a better visual

Notebook desenvolvido como avaliação da disciplina Introdução à Inteligência Artificial. O mesmo contempla partes de pré-processamento das bases de dados e o desenvolvimento dos algoritmos Multilayer Perceptron (MLP), Random Forest, K-means e Agrupamento hierárquico

Explore cryptocurrency market trends with Python using unsupervised learning techniques. Using Jupyter Notebooks to implement K-means clustering and Principal Component Analysis (PCA) to analyze and predict price trends of cryptocurrencies over 24-hour and 7-day periods.