

Calculating derivatives in PyTorch, automate your ML development pipeline with PyCaret, a video restoration transformer, adapting CV models for time series and automated EEG review, DALL-Eval, EvoJAX, and more ...
We believe that any data scientist and ML professional should never stop learning. In this post, we provide an overview of the best resources and courses you can use to start digging in.
Kubeflow pipeline from scratch, financial text classification using FinBERT, a single model for many visual modalities, a gentle introduction to supervised learning, GAN-based facial editing of real videos, NN-SVG, GreaseLM, Data2vec, videos, and more ...