Predicting the price of a football player using Machine Learning Algorithms
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Updated
Nov 29, 2021 - Jupyter Notebook
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.
An R package for regularized weight based SCA and PCA
SARIMAX model for forecast traffic volume
This is about Treue Technologies Data science Internship tasks.
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.
Linear Regression Models on Montesinho Forest Fire
This repository explores and compares different regression models for predicting continuous outcomes. This repository includes implementations and evaluations of five key regression models. The primary goal is to demonstrate how each model works, evaluate their performance using R-squared values, and guide users in selecting the best model.
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.
A dredge function to select the best models through an exhaustive combination of parameters.
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