GitHub topics: tranfer-learning

Repositories

ziadelsayed0/MachineLearning-DeepLearning

FineTuning LLMs and MLs models

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codewithdark-git/DocGPT

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.

Language: Python - Size: 32.2 KB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 1 - Forks: 1

ThanhHung2112/LMS_NextGen

An AI assistant for a Learning Management System (LMS)

Language: PHP - Size: 157 MB - Last synced at: 6 months ago - Pushed at: about 1 year ago - Stars: 12 - Forks: 2

UWNETLAB/dcss_supplementary

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

Language: HTML - Size: 436 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 18 - Forks: 9

aqibsaeed/On-device-activity-recognition

Personalized machine learning on the smartphone

Language: Java - Size: 107 MB - Last synced at: 12 days ago - Pushed at: about 2 years ago - Stars: 59 - Forks: 18

ZJUFanLab/scSpace

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

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AnMol12499/CropcareAI

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

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Adeolujoseph/FOOD_101-Classification-Using-Transfer-Learning-EfficientNet-model-

classifying the food101 dataset using cnn

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imostafizur/CSE498R

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

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JCRUNA/DeepLearningWithPython

Repositorio enfocado mostrar herramientas de Deep learning y ejemplos de uso.

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CommissarMa/pytorch-CRAFT

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。

Language: Python - Size: 1.45 MB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 37 - Forks: 10

KIRANKUMAR7-P/Deep_learning

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.

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Etienne-bobo/food101_classification_tensorflow

The model employs mixed-precision training within the TensorFlow framework, utilizing transfer learning techniques that encompass both feature extraction and fine-tuning stages. This approach is executed on the EfficientNetB0 architecture

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SD2k02/Sentiment-Analysis

This project focuses on classifying the sentiment of the given customer review.

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deepak2233/Waste-or-Garbage-Classification-Using-Deep-Learning

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.

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DesignofIntelligence/NLP-Disaster-Tweets-With-5-Architectures

Architectures: Naive Bayes, 1D CNN, RNNs LSTM, RNNs Bidirectional, RNNs GRU, Using transfer learning

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shercostiniano/filipino-stoytelling-ner

Open-source repository for our paper in Thesis 1

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llyx97/TAMT

[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

Language: Python - Size: 2.9 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 11 - Forks: 1

AbdulRasheed6/MobileNetV2

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

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femilgithub/Emo-tify

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Ellie190/Smart-Surveillance-Capstone-Project-

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

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tetaniarizki/transferlearning

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.

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