General Assembly's 2015 Data Science course in Washington, DC

Machine Learning notebooks for refreshing concepts.

Local Interpretable Model-Agnostic Explanations (R port of original Python package)

🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.

an MLOps/LLMOps platform

CloudCV GSoC Ideas

UBC ARBERT and MARBERT Deep Bidirectional Transformers for Arabic

Measure and visualize machine learning model performance without the usual boilerplate.

Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn.

a comprehensive statistical framework for detecting circular reasoning bias in AI algorithm evaluation

Flexible tool for bias detection, visualization, and mitigation

A High-level Scorecard Modeling API | 评分卡建模尽在于此

An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering, hyperparameter optimization, model evaluation, and cross-validation with a variety of ML techniques and MLP

An Interactive Approach to Understanding Deep Learning with Keras

This project analyzes and visualizes the Used Car Prices from the Automobile dataset in order to predict the most probable car price

Valor is a lightweight, numpy-based library designed for fast and seamless evaluation of machine learning models.

Evaluate the performance of computer vision models and prompts for zero-shot models (Grounding DINO, CLIP, BLIP, DINOv2, ImageBind, models hosted on Roboflow)

🎓 2020 Undergraduate Graduation Project in Jiangnan University ALL codes including Data-convert, keras-Train, model-Evaluate and Web-App

Use AutoAI to detect fraud

Benchmark evaluating LLMs on their ability to create and resist disinformation. Includes comprehensive testing across major models (Claude, GPT-4, Gemini, Llama, etc.) with standardized evaluation metrics.