Personalized machine learning on the smartphone

This model is created using pre-trained CNN architecture (VGG16 and RESNET50) via Transfer Learning that classifies the Waste or Garbage material (class labels =7) for recycling.

本项目旨在以CRAFT提供的预训练模型为基础，进行迁移学习以用于检测自己数据集中的文本。

An AI-driven platform offering crop recommendations, fertilizer suggestions, and disease detection for optimal farming

an integrative algorithm to distinguish spatially variable cell subclusters by reconstructing cells onto a pseudo space with spatial transcriptome references

Supplementary materials for McLevey 2021 Doing Computational Social Science (Sage, UK).

An AI assistant for a Learning Management System (LMS)

[NAACL 2022] "Learning to Win Lottery Tickets in BERT Transfer via Task-agnostic Mask Training", Yuanxin Liu, Fandong Meng, Zheng Lin, Peng Fu, Yanan Cao, Weipinng Wang, Jie Zhou

Open-source repository for our paper in Thesis 1

My notes for machine learning and deep learning

A Deep Learning.ai Coursera assignment, as part of the Google ML Bootcamp 2022

This repository contains my project for computer vision.

My graduation project from FCI-ZU computer science department

DocGPT (Doctor GPT) is an advanced medical diagnosis system that combines Vision Transformer (ViT) based deep learning models with LangChain agents to provide comprehensive medical image analysis and detailed diagnostic reports. The system leverages the power of PyTorch for deep learning and Groq's LLM for generating human-like medical insights.

Final year Capstone Research Project Titled: Smart Surveillance Implementation Study: Convolutional Neural Network, Facial Recognition, and Quantitative Analysis

This is Medical AI Research Work for CSE499 and 498R.

Emoji Prediction using Tranfer Learning(NLP)

This repository contains trained model, the training script and the dataset for Transfer Learning CNN model to recognize Bugatti La Voiture Noire.

www.dana.id

This is sub bab of Course Convolutionan Neural Network (CNN) with Tensorflow. And in this code, I use a technique called `Transfer Learning` in which utilize an already trained network to help solve a similar problem to the one it was originally trained to solve.