The "Object Detection and Identification Model" is an AI project employing YOLO v3, a pretrained model, and Python. It enables efficient and accurate detection and identification of objects in images, showcasing the prowess of advanced computer vision technology.

A concept on how Machine Learning (ML) can be integrated on Web apps

Landmark Detection using pre-trained models.

A semester project using ShuffleNet, MobileNetV3 Small & ResNet50 to classify real and fake faces with the specified dataset that taken from Kaggle.

Using deep learning models to accurately classify pet images into different breeds and types, demonstrating effective image classification and model evaluation.

Welcome to a diverse collection of hands-on ML, AI, Python, and Data Science projects. Explore and learn through practical applications. Happy coding! 🚀

Registration of pre-trained models found on Hugging Face using blockchain technology

Testing methods in PTM enabled OSS

Compare image similarity using features extracted from the pre-trained VGG16 model. This project leverages cosine similarity for accurate visual similarity assessment, making it ideal for image retrieval and duplicate detection.

dis-cyril is an Alexa like using pre-trained models and buzin.

Fine-tuning GPT-2 models with custom text corpora, utilizing Hugging Face's Transformers library and advanced training techniques for sophisticated text generation applications.

Streamlit app that predicts if a painting is a van Gogh

The code repository for "Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning"(CVPR24) in PyTorch.

🎉 PILOT: A Pre-trained Model-Based Continual Learning Toolbox

Collection of awesome parameter-efficient fine-tuning resources.

[ICML2024] Unified Training of Universal Time Series Forecasting Transformers