Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.

• UpdatedFeb 16, 2026
• Python

Resources of our survey paper "Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies"

• UpdatedSep 11, 2025

CLIP as a service - Embed image and sentences, object recognition, visual reasoning, image classification and reverse image search

• UpdatedJul 29, 2025
• Jupyter Notebook

Accelerating AI Training and Inference from Storage Perspective (Must-read Papers on Storage for AI)

• UpdatedDec 17, 2025

EmbeddedLLM: API server for Embedded Device Deployment. Currently support CUDA/OpenVINO/IpexLLM/DirectML/CPU

• UpdatedOct 6, 2024
• Python

Streamlining the process for seamless execution of PyCoral in running TensorFlow Lite models on an Edge TPU USB.

• UpdatedApr 12, 2024
• Python

Генерация описаний к изображениям с помощью различных архитектур нейронных сетей

• UpdatedMay 13, 2023
• Jupyter Notebook

😊📸 Real-Time Facial Emotion Recognition using Deep Learning 🤖🧠

• UpdatedApr 22, 2025
• Python

The primary objective of this project was to build and deploy an image classification model for Scones Unlimited, a scone-delivery-focused logistic company, using AWS SageMaker.

• UpdatedJan 24, 2023
• HTML

Image Classifiers are used in the field of computer vision to identify the content of an image and it is used across a broad variety of industries, from advanced technologies like autonomous vehicles and augmented reality, to eCommerce platforms, and even in diagnostic medicine.

• UpdatedMar 1, 2023
• HTML

Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.

• UpdatedMay 6, 2024
• Jupyter Notebook

Deep learning solution for apple disease detection using CNN architecture. Trained on PlantVillage dataset to classify 4 apple leaf conditions with real-time image analysis.

• UpdatedJan 1, 2026
• Python

A personal journey into model inference engineering — learning, building, and sharing along the way.

• UpdatedAug 15, 2025
• Jupyter Notebook

Successfully developed a fine-tuned DistilBERT transformer model which can accurately predict the overall sentiment of a piece of financial news up to an accuracy of nearly 81.5%.

• UpdatedMay 6, 2024
• Jupyter Notebook

• UpdatedOct 30, 2024
• Python

This project is a web-based application that uses a pre-trained Mask R-CNN model to detect and classify car damage types (scratch, dent, shatter, dislocation) from images. Users can upload an image of a car, and the application will highlight damaged areas with bounding boxes and masks, providing a clear visual representation of the detected damage

• UpdatedAug 31, 2024
• Jupyter Notebook

A cloud run function to invoke a prediction against a machine learning model that has been trained outside of a cloud provider.

• UpdatedJan 19, 2025
• Python

Example distributed system for ML model inference by using Kafka, including spring boot REST+JPA server with Java consumer program

• UpdatedNov 23, 2025
• Java

Successfully fine-tuned a pretrained DistilBERT transformer model that can classify social media text data into one of 4 cyberbullying labels i.e. ethnicity/race, gender/sexual, religion and not cyberbullying with a remarkable accuracy of 99%.

• UpdatedJun 10, 2024
• Jupyter Notebook

Experimental web application demonstrating how an offline-trained financial fraud detection model can be exposed through a web interface. Built with Flask and a pre-trained XGBoost model to showcase ML inference flow, feature engineering, and result communication — not a production fraud prevention system.

• UpdatedJan 24, 2026
• HTML