About
DL4J takes advantage of the latest distributed computing frameworks including Apache Spark and Hadoop to accelerate training. On multi-GPUs, it is equal to Caffe in performance. The libraries are completely open-source, Apache 2.0, and maintained by the developer community and Konduit team. Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API. Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs. There are a lot of parameters to adjust when you're training a deep-learning network. We've done our best to explain them, so that Deeplearning4j can serve as a DIY tool for Java, Scala, Clojure, and Kotlin programmers.
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About
Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.
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About
MATLAB® combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented. MATLAB apps let you see how different algorithms work with your data. Iterate until you’ve got the results you want, then automatically generate a MATLAB program to reproduce or automate your work. Scale your analyses to run on clusters, GPUs, and clouds with only minor code changes. There’s no need to rewrite your code or learn big data programming and out-of-memory techniques. Automatically convert MATLAB algorithms to C/C++, HDL, and CUDA code to run on your embedded processor or FPGA/ASIC. MATLAB works with Simulink to support Model-Based Design.
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About
The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Researchers, developers and professionals requiring an open-source, distributed, deep learning library for the JVM
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Audience
Developers interested in an deep learning API solution to minimize the number of user actions required for common use cases
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Audience
Modeling, simulation, and programming software that can be hosted in the cloud or on-premise
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Audience
Developers interested in a beautiful but advanced programming language
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationDeeplearning4j
Founded: 2019
Japan
deeplearning4j.org
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Company InformationKeras
United States
keras.io
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Company InformationThe MathWorks
Founded: 1984
United States
www.mathworks.com
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Company InformationPython
Founded: 1991
www.python.org
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Categories |
Categories |
Categories |
Categories |
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Deep Learning Features
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
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CAD Features
2 1/2-Axis Milling
2D Drawing
3-Axis Milling
3D Modeling
4-Axis Milling
5-Axis Milling
Civil
Collaboration
Database Connectivity
Design Analysis
Design Export
Document Management
Electrical
Hole Making
Mechanical
Mechatronics
Presentation Tools
Simulate Cycles
Spiral Output
Structural Engineering
Toolpath Simulation
User Defined Cycles
Engineering Features
2D Drawing
3D Modeling
Chemical Engineering
Civil Engineering
Collaboration
Design Analysis
Design Export
Document Management
Electrical Engineering
Mechanical Engineering
Mechatronics
Presentation Tools
Structural Engineering
Financial Risk Management Features
Compliance Management
Credit Risk Management
For Hedge Funds
Liquidity Analysis
Loan Portfolio Management
Market Risk Management
Operational Risk Management
Portfolio Management
Portfolio Modeling
Risk Analytics Benchmarks
Stress Tests
Value At Risk Calculation
Simulation Features
1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling
Statistical Analysis Features
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization
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Integrations
Algoreus
Apache TinkerPop
Bitfount
ChatKit
DataChain
Databricks Data Intelligence Platform
Files.com
Filigran
Flexprice
Gurobi Optimizer
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Integrations
Algoreus
Apache TinkerPop
Bitfount
ChatKit
DataChain
Databricks Data Intelligence Platform
Files.com
Filigran
Flexprice
Gurobi Optimizer
|
Integrations
Algoreus
Apache TinkerPop
Bitfount
ChatKit
DataChain
Databricks Data Intelligence Platform
Files.com
Filigran
Flexprice
Gurobi Optimizer
|
Integrations
Algoreus
Apache TinkerPop
Bitfount
ChatKit
DataChain
Databricks Data Intelligence Platform
Files.com
Filigran
Flexprice
Gurobi Optimizer
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