Personalized machine learning on the smartphone

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。

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.

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).

[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

An AI assistant for a Learning Management System (LMS)

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

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

My graduation project from FCI-ZU computer science department

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 repository contains my project for computer vision.

Welcome to my Deep Learning Showcase repository! Explore insightful projects including ATM Data Analysis powered by ANN and Rice Image Classification using various CNN architectures like Vanilla CNN, VGG-16, and fine-tuning techniques. Join me in unraveling data-driven stories and pushing the boundaries of image classification.

Regularized and extrapolative season-to-season transfer for scene adaptation

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.