The aim of this project is to develop a solution using Data science and machine learning to predict the compressive strength of a concrete with respect to the its age and the quantity of ingredients used.
GPL-3.0 License
Web-interface + rest API for classification and regression (https://jeff1evesque.github.io/machin...
2Waffles.Ai - An innovative dual-powered, intelligent assistant AI CRM assistant designed to enha...
A robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for Sec...
This project features a web app that predicts house prices using a linear regression model. Users...
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Example Python package to demonstrate how to publish packages on PyPI
A Flask LIME explainer app for fine-grained sentiment classification.
Developed a sophisticated machine learning model capable of generating diverse interview question...
The project's goal is to help job seekers understand the basic qualifications for specific jobs a...
In this repository, I will share some useful notes and references about deploying deep learning-b...
Predict Energy Output of a wind turbine at any geo-coordinate for a time-series of next 72 hours ...
Specialization in Python with flask towards Data Science
Robust credit risk model that go beyond traditional credit scoring methods in banks
Master's thesis on Big Data