螺旋熵减系统

螺旋熵减理论

Code supplement for "Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction"

for various machine learning projects

Task-2 Completed as a DSBA Intern @ The Sparks Foundation

In this section, we will examine unsupervised learning algorithms in machine learning.

This repository contains the code and analysis for a research project aimed at enhancing social media impact for food safety security organizations. The project focuses on understanding text tone preferences based on user demographics using machine learning techniques.

repo contains sample code snippets on #ML, #DeepLearning, #GenAI topics

Multimodal Unsupervised Machine Translation and Unsupervised Representation Learning for high-level model interpretability.

Stylometry approach detecting writing patterns and changings using NLTK, XML-roBERTa, Gensim topic modelling and unsupervised-PCA learning

The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation

Free lectures on Machine learning which covers core topics and models on supervised and unsupervised, machine learning.

Recommender implemented using unsupervised machine learning, web scraping, and APIs to deliver personalized song recommendations. Utilizing clustering analysis on song features and data extraction techniques via web scraping and APIs, it provides tailored suggestions based on user input.

AI | ML | DL Fully Covered for Basic

The projects here demonstrate how a textual corpus is prepared for analysis, preprocessing steps for computational text mining and extraction of business insights. Concepts such as feature representation using bag of words and TF-IDF are demonstrated, clustering and supervised machine learning algorithms like regression and others are used on a DTM

This is a Breast Cancer Detection project with unsupervised learning algorithmic approaches alongside Naive Bayes Classifier Algorithm, Logistic Regression and GaussianNB.

Machine Learning Tasks

Based on a user's preferred movie or TV show, Unsupervised Machine Learning-Netflix Recommender suggests Netflix movies and TV shows. These suggestions are based on a K-Means Clustering model. These algorithms base their recommendations on details about movies and tv shows, such as their genres and description.

Nonnegative Matrix Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning

Fast and explainable clustering in Python