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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. CUDA vs Skyl.ai

CUDA vs Skyl.ai

OverviewComparisonAlternatives

Overview

CUDA
CUDA
Stacks542
Followers215
Votes0
Skyl.ai
Skyl.ai
Stacks0
Followers7
Votes0

Skyl.ai vs CUDA: What are the differences?

What is Skyl.ai? Manage your Complete Machine Learning Workflow. Build & deploy ML models faster on unstructured data. No specialized skills required Easy-to-use & scalable SaaS platform..

What is CUDA? It provides everything you need to develop GPU-accelerated applications. 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.

Skyl.ai and CUDA can be primarily classified as "Machine Learning" tools.

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Detailed Comparison

CUDA
CUDA
Skyl.ai
Skyl.ai

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.

Build & deploy ML models faster on unstructured data. No specialized skills required. Easy-to-use & scalable SaaS platform.

-
Collect, label, and visualize unstructured data; Guided modules to upload, clean, label, and visualize unstructured data; Create & train models automatically; Train models without coding using our ready-made, fine tuned, state-of-the-art neural network architecture; Monitor model performance and iterate in minutes; Monitor data collection, labeling, training, and performance of deployed models in real-time
Statistics
Stacks
542
Stacks
0
Followers
215
Followers
7
Votes
0
Votes
0

What are some alternatives to CUDA, Skyl.ai?

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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