Music album popularity prediction classic ML model showcasting MLOps, versioning, feature selection, cross valdiation and concept drift.

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Classifying whether an asteroid is hazardous or not.

XGBoost (Extreme Gradient Boosting) is a highly efficient and accurate machine learning algorithm based on gradient boosting, excelling in structured data tasks. It includes features like regularization, handling missing values, and parallel processing. Widely used in competitions and industry, it supports multiple programming languages.

This code demonstrates the use of machine learning to model the multimodal nature of a single cell. Using machine learning to predict RNA from DNA, that is, using chromatin accessibility data to predict the RNA gene expression and to predict surface protein from RNA, that is, using RNA sequence data to predict surface protein levels in a cell

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Recommender system using XGBOOST, Neural_Network, Ensemble and LGBM

Simple and flexible classical ML module that can be used for recording baseline ML performance.

Distributed ML Training and Fine-Tuning on Kubernetes

Predicting bank churn rates with machine learning models (decision trees, random forest, & xgboost)

Batch Name: MIP-ML-11 (Machine Learning Intern)

Time series forecasting with scikit-learn models

An end-to-end Data Science Project to optimize Operations team daily activities.

Catch Phisher is a comprehensive phishing detection kit enhanced with intelligent surveillance capabilities. The solution includes a web app, a browser extension, and the Phish Guard assistant, providing multi-layered protection against phishing. The browser extension acts as a real-time monitor, scanning URLs and cross-checking them with a db.

A Gradio machine learning application that predicts Danish car prices. Project includes web scraping, feature engineering, model creation and deployment

Contains Many Machine Learning Algorithms Which I train during My coursework & Challenges.

Standardized Serverless ML Inference Platform on Kubernetes

📝 Examples of how to use Neptune for different use cases and with various MLOps tools

EHRM [ Electronic Health Record Management ] introduces a centralized platform for analyzing patient records, offering insights into billing amounts, demographics, prevalent diagnoses, medical conditions, consulted doctors, admission types, and medication usage.

📘 The MLOps stack component for experiment tracking