Standardized Serverless ML Inference Platform on Kubernetes

To predict whether a user will click on ad or not.

ML hyperparameters tuning and features selection, using evolutionary algorithms.

👻 Набор ноутбуков по ML "на все случаи жизни". Позже превращу его в ROADMAP

A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.

A dashboard and prediction model based on the AdventureWorks 2019 dataset, completely free to use.

Prompt Based video navigation project, Here user can provide a video link and a prompt specific to what they want to find in video & can efficiently navigate the video.

To predict client subscription to term deposits and optimize marketing strategies by identifying potential subscribers.

ML based project which uses various techniques to build a hybrid model for identifying brain tumour in MRI images

Machine leaning predictive model for Covid-19 recovery time. Dataset "Casos positivos de COVID-19 en Colombia" from Datos Abiertos Colombia is used.

Ashley Bythell - Python

"Wind Power Predictor" is a machine learning project that forecasts turbine output using real-time data from Turkish wind farms. Its web app interface offers convenient access to predictions, enabling informed decisions for maximizing energy production and advancing renewable energy usage.

This project is part of a senior year Capstone project at the New York University. The project is in collaboration with the ComNets. The goal of the project is to implement a machine learning model into a browser to accelerate mobile web pages.

Estimate future qualifying results using ML

Data-driven Autonomous FPL manager using Gradient Boosted trees

This project improves information retrieval by detecting duplicate question pairs in the Quora dataset using data exploration, text preprocessing, feature engineering, and models like Random Forest and LSTM, aiming to streamline question-answering.

Tools for easing the handoff between AI/ML and App/SRE teams.

This project explores the optimal combination of Bag-of-Words and TF-IDF vectorization with Naive Bayes and SVM for sentiment analysis. It evaluates performance using accuracy, precision, recall, and F1-score, addressing ethical concerns like data privacy and bias to improve sentiment classification in real-world applications.

This repository is dedicated to showcasing the academic projects completed during my Master in Data Science & AI. The main objective is to show a collection of projects in various data science fields, including: data cleaning & preprocessing, data analysis, data visualization, machine learning, clustering, among others.