Implementation of algorithms such as normal equations, gradient descent, stochastic gradient descent, lasso regularization and ridge regularization from scratch and done linear as well as polynomial regression analysis. Implementation of several classification algorithms from scratch i.e. not used any standard libraries like sklearn or tensorflow.

Proyecto de investigación en ML para identificar factores genéticos en pronóstico de lesiones pre-tumorales. Aprendizaje no supervisado para discernir perfiles genéticos distintivos entre grupos de buen y mal pronóstico, mejorando detección y tratamiento temprano del cáncer.

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

This is my final year project "customer reviews classification and analysis system using data mining and nlp". It analyzes and then classifies the customer reviews on the basis of their fakeness, sentiments, contexts and topics discussed. The reviews are taken from various e-commerce platforms like daraz and amazon.

AI model for summarizing and categorizing news articles

Using text analytics to understand cultural patterns in philosophical texts. Exploring gender, author, region, and time-period differences, and extracting key philosophical concepts.

Topic modeling is a text mining technique in which an algorithm is applied to a large corpus of documents that identifies patterns of word co-occurrence. These patterns of word co-occurrence are conceptualized as “topics” which can be used to discover latent structures in the corpus, to group similar documents together.

solving problems with data analysis, hypotheses and the most used statistical tests in ecology

**Odio oído** es una herramienta predictiva. Trackeamos el riesgo de toxicidad en Twitter por país 24/7

Dive into the world of Machine Learning in this immersive lab course, exploring open-source tools and algorithms such as random forest, SVM, linear regression, PCA, K-means, LDA, KNN, decision tree, and more. Engage in real-world ML projects and deploy your models, gaining practical experience in the forefront of AI technology.

My published paper on the application of LDA on documents. Base corpus: Thousands of LDS General Conference articles spanning decades.

A topic detection project

Machine Learning Library for Classification Tasks

This project aims to build a complete pattern recognition system to solve classification problems using the k-Nearest Neighbors (KNN) algorithm. To classify chest X-ray images into three categories: COVID-19 positive, pneumonia positive, and normal. To achieve this, we utilize the COVID-19 Chest X-ray dataset available on Kaggle.

LDA, BERTopic and bipartite network for topic modeling

Python code: Uses LDA for topic modeling on text data.

Facial Recognition system with AI and Statistical Learning models

Uncovering Patterns in Stack Exchange Data