Using AWS s3,SQL,python and Pyspark, build data pipelines to provide the analytics department with the required formatted data

Adding row and column highlighting to an ASP.NET Gridview.

tdast typescript typings

⭐ Kyivstar Big Data School 5.0 task of 2'nd stage of the selection

Dataframe to tensor converter for deep learning.

Kaggle - Mechanisms of Action (MoA) Prediction

Data Model for Investing Applications

Use ensembling and Optuna to solve the Saceship Titanic competition.

Covid-19 data from Tuscany and its provinces from 24/2/2020 to 15/6/2022

Data Utility Improvement Experiment for DECAF

This project aims to use k-means and Agglomerative clustering to segment customers into different groups based on their characteristics and purchasing habits. The goal is to understand the similarities and differences between the customer segments, which can help inform marketing strategies and target specific groups of customers.

Researching how old classical machine learning – gradient boosting – and new modern deep learning algos cope with tabular data

A simple repository with PCA, Deep Learning and Clustering techniques to identify persona in a survey dataset.

Tabular machine learning simplified!

Various Python programs working with CSV and tabular data

Predicting how capable each applicant is of repaying a loan?

My experiments on the rossmann dataset

Gaussian process applied to tabular models (implemented with fastai)

Statistics and Quantitative Analysis Library for C++. Squall provides a set of robust, high-performance and easy to use tools for managing, manipulating & reshaping datasets, calculating statistics, aggregating data, extracting subsets and much more. Squall contains 4 header files only and is easy to implement into any existing C++ project.