Predicting the price of a football player using Machine Learning Algorithms

A project to predict the average prices of Avocado in USA.

This is a Premiere Project done by Team Gitlab in Hamoye Data Science Program Dec'22. Out of 5 models used on the data, Random Forest Classifier was used to further improve the prediction of characters death. With parameter tuning and few cross validation, we were able to reduce the base error by 5.42% and increase accuracy by 2,42%.

This repo is for copula based analysis on bivariate as well as multivariate data sets in ecology and related fields. For details and citation we refer to this publication: Ghosh et al., Advances in Ecological Research, vol 62,pp 409, 2020

Determine a Prototype from a number of runs of Latent Dirichlet Allocation.

Detecting Damped Lyman-alpha Absorbers (DLAs) with Gaussian Processes

ML4SCI hackathon NMR spin challenge winning project. Training machine learning models for multi-target regression problem.

This project explores machine learning techniques, focusing on data preprocessing, model building, and evaluation. It includes data analysis, visualization, various algorithms, and performance comparison. Key topics: data cleaning, feature engineering, model selection, hyperparameter tuning, and evaluation metrics.

An R package for regularized weight based SCA and PCA

Deep Learning notes and practical implementation with Tensorflow and keras. Text Analytics and practical application implementation with NLTK, Spacy and Gensim.

SARIMAX model for forecast traffic volume

This has been a machine learning quest to classify cancer types using gene expression data, utilizing powerful tools and techniques to preprocess, train and evaluate models. The ultimate goal, to save lives through early diagnosis with high accuracy and precision.

This is about Treue Technologies Data science Internship tasks.

Predicting compressive strength of concrete using machine learning models with featurization and Hyper parameter tuning

It calculates the accuracy score and confusion matrix for a logistic regression model. The dataset is about coupon used or not in an apparel store known as Simmons .

Integrated robust and reliable ML Pipelines for Research and Production environment

Check my projects related to ML feature engineering and modeling.

Linear Regression Models on Montesinho Forest Fire