Deep Learning Environments

Deep Learning and Tensors

The Deep Learning and Tensors environments are designed for specific deep learning libraries and tools. These include environments for PyTorch, JAX, TensorFlow, Hugging Face, and, each equipped with the necessary tools for efficient deep learning and tensor computations. They provide a streamlined experience for tasks such as training neural network models, high-performance numerical computing, and large-scale machine learning.

Environment Description Quickstart
torch Environment equipped with PyTorch, a powerful open-source tensor library for training neural network models written for Python. Open In American Data Science
jax Environment set up for JAX, a library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning. Open In American Data Science
tensorflow Environment designed for TensorFlow, an end-to-end open-source tensor library for deep learning in Python. Open In American Data Science
huggingface Environment optimized for Hugging Face tools like transformers, datasets, accelerate, and optimum powered by PyTorch. Open In American Data Science
fastai Environment for tools and PyTorch, ideal for training and running inference on neural network models. Open In American Data Science