Machine learning playground

Collection of projects used for learning new concepts.
The models are implemented in PyTorch.

Structure

Computer vision

Image classification
- Doing binary/multi-class classification.
Models
- Implementing SOTA convolutional neural networks.
Object detection
- Implementing YOLO, SSD, RetinaNet and Faster R-CNN.
Semantic segmentation
- Implementing FCN-8 and U-Net.
Neural style transfer
- Implementing a neural algorithm for artistic style.
Generative models
- Implementing DCGAN, Wasserstein GAN, VAE and Conditional VAE.

Natural language processing

Sentiment analysis
- Doing sentiment analysis using different pre-trained methods: word-embeddings, BERT.
Text synthesis
- Synthesis text (character level).
word2vec
- Implementing word2vec.
Speech classification
- Classifying speech commands.

Additional

Collaborative filtering
- Implementing collaborative filtering.
Entity embedding
- Implementing entity embeddings.
Quantization
- Quantize a cnn model.
Pruning
- Pruning a cnn model.