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  1. Stackups
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  4. Machine Learning Tools
  5. CUDA vs Pytorch Lightning

CUDA vs Pytorch Lightning

OverviewComparisonAlternatives

Overview

CUDA
CUDA
Stacks542
Followers215
Votes0
Pytorch Lightning
Pytorch Lightning
Stacks17
Followers15
Votes0

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Detailed Comparison

CUDA
CUDA
Pytorch Lightning
Pytorch Lightning

A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.

It makes coding complex neural networks simple. Spend more time on research, less on engineering. It is fully flexible to fit any use case and built on pure PyTorch so there is no need to learn a new language.

-
Run your code on any hardware; Performance & bottleneck profiler; Model checkpointing; 16-bit precision; Run distributed training; Logging; Metrics; Visualization; Early stopping
Statistics
Stacks
542
Stacks
17
Followers
215
Followers
15
Votes
0
Votes
0
Integrations
No integrations available
PyTorch
PyTorch
Python
Python

What are some alternatives to CUDA, Pytorch Lightning?

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

scikit-learn

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

Kubeflow

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

Polyaxon

Polyaxon

An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.

Streamlit

Streamlit

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

MLflow

MLflow

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

H2O

H2O

H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.

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