/ml_playground

Collection of machine learning projects

Primary LanguageJupyter Notebook

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.
  • Tokenizer
    • Implementing BPE tokenizer.

Additional

  • Collaborative filtering
    • Implementing collaborative filtering.
  • Entity embedding
    • Implementing entity embeddings.
  • Quantization
    • Quantize a cnn model.
  • Pruning
    • Pruning a cnn model.
  • Transformers
    • Implementing a Transformer from scratch.