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Description
Keras is an API tailored for human users rather than machines. It adheres to optimal practices for alleviating cognitive strain by providing consistent and straightforward APIs, reducing the number of necessary actions for typical tasks, and delivering clear and actionable error messages. Additionally, it boasts comprehensive documentation alongside developer guides. Keras is recognized as the most utilized deep learning framework among the top five winning teams on Kaggle, showcasing its popularity and effectiveness. By simplifying the process of conducting new experiments, Keras enables users to implement more innovative ideas at a quicker pace than their competitors, which is a crucial advantage for success. Built upon TensorFlow 2.0, Keras serves as a robust framework capable of scaling across large GPU clusters or entire TPU pods with ease. Utilizing the full deployment potential of the TensorFlow platform is not just feasible; it is remarkably straightforward. You have the ability to export Keras models to JavaScript for direct browser execution, transform them to TF Lite for use on iOS, Android, and embedded devices, and seamlessly serve Keras models through a web API. This versatility makes Keras an invaluable tool for developers looking to maximize their machine learning capabilities.
Description
Luminal is a high-performance machine-learning framework designed with an emphasis on speed, simplicity, and composability, which utilizes static graphs and compiler-driven optimization to effectively manage complex neural networks. By transforming models into a set of minimal "primops"—comprising only 12 fundamental operations—Luminal can then implement compiler passes that swap these with optimized kernels tailored for specific devices, facilitating efficient execution across GPUs and other hardware. The framework incorporates modules, which serve as the foundational components of networks equipped with a standardized forward API, as well as the GraphTensor interface, allowing for typed tensors and graphs to be defined and executed at compile time. Maintaining a deliberately compact and modifiable core, Luminal encourages extensibility through the integration of external compilers that cater to various datatypes, devices, training methods, and quantization techniques. A quick-start guide is available to assist users in cloning the repository, constructing a simple "Hello World" model, or executing larger models like LLaMA 3 with GPU capabilities, thereby making it easier for developers to harness its potential. With its versatile design, Luminal stands out as a powerful tool for both novice and experienced practitioners in machine learning.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Akira AI
Yes
AutoKeras
Yes
BentoML
Yes
Cleanlab
Yes
Comet
Yes
Comet LLM
Yes
Databricks
Yes
Dragonfly 3D World
Yes
Flower
Yes
GPUEater
Yes
Integrations
Akira AI
No
AutoKeras
No
BentoML
No
Cleanlab
No
Comet
No
Comet LLM
No
Databricks
No
Dragonfly 3D World
No
Flower
No
GPUEater
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Keras
Country
United States
Website
keras.io
Vendor Details
Company Name
Luminal
Country
United States
Website
luminalai.com
Product Features
Deep Learning
Convolutional Neural Networks
Yes
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
Yes
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No