TensorBoard

TensorBoard

Tensorflow
+

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About

The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow. Kubeflow provides a custom TensorFlow training job operator that you can use to train your ML model. In particular, Kubeflow's job operator can handle distributed TensorFlow training jobs. Configure the training controller to use CPUs or GPUs and to suit various cluster sizes. Kubeflow includes services to create and manage interactive Jupyter notebooks. You can customize your notebook deployment and your compute resources to suit your data science needs. Experiment with your workflows locally, then deploy them to a cloud when you're ready.

About

TensorBoard is TensorFlow's comprehensive visualization toolkit designed to facilitate machine learning experimentation. It enables users to track and visualize metrics such as loss and accuracy, visualize the model graph (operations and layers), view histograms of weights, biases, or other tensors as they change over time, project embeddings to a lower-dimensional space, and display images, text, and audio data. Additionally, TensorBoard offers profiling capabilities to optimize TensorFlow programs. These features collectively provide a suite of tools to understand, debug, and optimize TensorFlow programs, enhancing the machine learning workflow. In machine learning, to improve something you often need to be able to measure it. TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. It enables tracking experiment metrics, visualizing the model graph, and projecting embeddings to a lower dimensional space.

About

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Anyone looking for a Machine Learning toolkit for Kubernetes

Audience

Developers looking for a solution to optimize their TensorFlow programs

Audience

Organizations interested in a powerful open source machine learning platform

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 4.5 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Kubeflow
www.kubeflow.org

Company Information

Tensorflow
United States
www.tensorflow.org/tensorboard

Company Information

TensorFlow
Founded: 2015
United States
www.tensorflow.org

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Categories

Categories

Categories

Machine Learning Features

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Integrations

Activeeon ProActive
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Comet LLM
Cyfuture Cloud
E2E Cloud
Flex83
Flyte
HStreamDB
Intel Tiber AI Studio
LaunchX
Mona
PostgresML
Quantiphi Conversational AI
Simplismart
TFLearn
V7 Darwin
Vertex AI Notebooks
Yandex Data Proc
spaCy

Integrations

Activeeon ProActive
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Comet LLM
Cyfuture Cloud
E2E Cloud
Flex83
Flyte
HStreamDB
Intel Tiber AI Studio
LaunchX
Mona
PostgresML
Quantiphi Conversational AI
Simplismart
TFLearn
V7 Darwin
Vertex AI Notebooks
Yandex Data Proc
spaCy

Integrations

Activeeon ProActive
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Comet LLM
Cyfuture Cloud
E2E Cloud
Flex83
Flyte
HStreamDB
Intel Tiber AI Studio
LaunchX
Mona
PostgresML
Quantiphi Conversational AI
Simplismart
TFLearn
V7 Darwin
Vertex AI Notebooks
Yandex Data Proc
spaCy
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