https://github.com/machinelearningzuu/ai-universe
In this repo I'm gonna implement any AI/ML/DL/RL/NLP/CV/GNN project I found 😇 anywhere. please provide if you have any new project ideas
https://github.com/machinelearningzuu/ai-universe
artificial-intelligence computer-vision deep-learning gans graphneuralnetwork machine-learning natural-language-processing pytorch reinforcement-learning tensorflow
Last synced: about 1 month ago
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In this repo I'm gonna implement any AI/ML/DL/RL/NLP/CV/GNN project I found 😇 anywhere. please provide if you have any new project ideas
- Host: GitHub
- URL: https://github.com/machinelearningzuu/ai-universe
- Owner: machinelearningzuu
- Created: 2022-12-06T15:26:42.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-02-04T09:47:48.000Z (over 3 years ago)
- Last Synced: 2025-05-28T15:07:23.033Z (about 1 year ago)
- Topics: artificial-intelligence, computer-vision, deep-learning, gans, graphneuralnetwork, machine-learning, natural-language-processing, pytorch, reinforcement-learning, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 164 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ai-universe
## 1 happy vs sad - image classification
Data Type - Image
Type of problem - Classification
dataset - https://www.kaggle.com/datasets/aravindanr22052001/emotiondetection-happy-or-sad
framework - tensorflow
model - Custom Convolutional Neural Network (ConvNet)
## 2 deep face detection
Data Type - Image
Type of problem - Object Detection
dataset - Here I created a dataset of my own and Annotated it using LABELME
framework - tensorflow
special libraries - Albumentations for data augmentation
- Labelme for annotation
model - VGG16 multi output model (One for bounding box and one for classification)
## 2 Capuchinbird audio detection
Data Type - Audio
Type of problem - Classification
dataset - https://www.kaggle.com/datasets/kenjee/z-by-hp-unlocked-challenge-3-signal-processing
framework - tensorflow
special libraries - Albumentations for data augmentation
- Labelme for annotation
model - VGG16 multi output model (One for bounding box and one for classification)