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Description

Declarative machine learning systems offer an ideal combination of flexibility and ease of use, facilitating the rapid implementation of cutting-edge models. Users concentrate on defining the “what” while the system autonomously determines the “how.” Though you can start with intelligent defaults, you have the freedom to adjust parameters extensively, even diving into code if necessary. Our team has been at the forefront of developing declarative machine learning systems in the industry, exemplified by Ludwig at Uber and Overton at Apple. Enjoy a selection of prebuilt data connectors designed for seamless compatibility with your databases, data warehouses, lakehouses, and object storage solutions. This approach allows you to train advanced deep learning models without the hassle of infrastructure management. Automated Machine Learning achieves a perfect equilibrium between flexibility and control, all while maintaining a declarative structure. By adopting this declarative method, you can finally train and deploy models at the speed you desire, enhancing productivity and innovation in your projects. The ease of use encourages experimentation, making it easier to refine models based on your specific needs.

Description

TensorFlow is a comprehensive open-source machine learning platform that covers the entire process from development to deployment. This platform boasts a rich and adaptable ecosystem featuring various tools, libraries, and community resources, empowering researchers to advance the field of machine learning while allowing developers to create and implement ML-powered applications with ease. With intuitive high-level APIs like Keras and support for eager execution, users can effortlessly build and refine ML models, facilitating quick iterations and simplifying debugging. The flexibility of TensorFlow allows for seamless training and deployment of models across various environments, whether in the cloud, on-premises, within browsers, or directly on devices, regardless of the programming language utilized. Its straightforward and versatile architecture supports the transformation of innovative ideas into practical code, enabling the development of cutting-edge models that can be published swiftly. Overall, TensorFlow provides a powerful framework that encourages experimentation and accelerates the machine learning process.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Python Yes 
Amazon EC2 Capacity Blocks for ML No 
Amazon EC2 Trn2 Instances No 
Apolo No 
Cerebrium No 
DagsHub No 
ExamRoom.AI No 
Flower No 
Interplay No 
Joget DX No 
Jovian No 
Modelbit No 
MySQL Yes 
PredictKube No 
SynapseAI No 
TFLearn No 
Xilinx No 
Yandex Data Proc No 
ZenML No 
io.net No 

Integrations

Python Yes 
Amazon EC2 Capacity Blocks for ML Yes 
Amazon EC2 Trn2 Instances Yes 
Apolo Yes 
Cerebrium Yes 
DagsHub Yes 
ExamRoom.AI Yes 
Flower Yes 
Interplay Yes 
Joget DX Yes 
Jovian Yes 
Modelbit Yes 
MySQL No 
PredictKube Yes 
SynapseAI Yes 
TFLearn Yes 
Xilinx Yes 
Yandex Data Proc Yes 
ZenML Yes 
io.net Yes 

Pricing Details

Pay-as-you-go pricing
Free Trial Yes 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Predibase

Country

United States

Website

predibase.com

Vendor Details

Company Name

TensorFlow

Founded

2015

Country

United States

Website

www.tensorflow.org

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools Yes 
Templates No 
Visualization Yes 

Alternatives

Alternatives