Compare Addepto и TensorFlow

Take a look at comparison of based on the customers reviews. The rating is calculated in real time from reviews of customers.

Starting price from 1 usd. from 1 usd.
Who this service is for

Process capability software that uses machine learning to measure the performance of processes.

An open-source platform that allows developers, businesses and researchers to build and deploy machine learning algorithms.

Rating
0 / 5
4.2 / 5
Machine Learning software features
Deep Learning
Model Training
Statistical Modeling
Deep Learning
Model Training
Statistical Modeling
Data Mining software features
Predictive Modeling
Predictive Modeling
IoT software features
Visualization
Visualization
Interface screenshot
Desktop & Mobile Platforms

Cloud-hosted / box software

Cloud-hosted / box software

Support Working hours, Online Working hours, Online
Training
Documentation
Webinars
Personal
Online
Documentation
Webinars
Personal
Online
Reviews
5 / 5

A Machine and Deep Learner must have Library

Benefits:

This Library is very flexible for doing Matrices and Tensor So building very deep high level but quick and scalable ready to use neural networks is... Read more

This Library is very flexible for doing Matrices and Tensor So building very deep high level but quick and scalable ready to use neural networks is at your finger tips. The added other Anaconda Library and Keras compatibility

Drawbacks:

Depreciation of the code is frustrating. To use one form just to throw a Error message.

Summary:

Scott W. D.
4 / 5

Relatively Straightforward Deep Learning Framework

Benefits:

The 2.0 version is easy to set up and there are a lot of APIs that are integrated for using various programming languages to do the same thing. I ... Read more

The 2.0 version is easy to set up and there are a lot of APIs that are integrated for using various programming languages to do the same thing. I personally have been using python with this application and have had very little problems getting going. There are a lot of tutorials on getting started, some good data available for free to assist with the learning process. Everything can be run locally which makes it easy to expand on-site. Cloud options are also affordable.

Drawbacks:

The learning curve is a bit steep. This isn't specifically an issue because of TensorFlow itself, the idea of neural networks are not simple. Ten... Read more

Summary:

Human pattern recognization, image recognization. Habits and trends.

Ben W.
3 / 5

Review of Google Cloud ML Engine

Benefits:

The feature of the Google Cloud ML Engine that I most like is the machine learning features that have been provided by this platform. The ML featur... Read more

The feature of the Google Cloud ML Engine that I most like is the machine learning features that have been provided by this platform. The ML features of this engine provide SOTA results in every task in machine learning and artificial intelligence. The ML features are very handy and easy to use and integrate in other applications as well. I would recommend everyone to use Google Cloud ML Engine for developing AI systems.

Drawbacks:

The pricing, when exceeded the free tier of Google Cloud ML platform, is high. The pricing is high compared to other services like Azure Cloud ML p... Read more

Summary:

My overall experience with Google Cloud ML platform was very good. I used it's machine learning services to integrate those in my web applications.

shushant p.
4 / 5

TensorFlow: The Root of all ML

Benefits:

TensorFlow is a very powerful framework, and with the new version and the Keras interface, it is 10 times much easier to use, for simple usage. Ear... Read more

TensorFlow is a very powerful framework, and with the new version and the Keras interface, it is 10 times much easier to use, for simple usage. Earlier it used to require a deeper level of understanding to use the library, but now it is very fluid, simple, and at the same time effective.

Drawbacks:

Even though the Keras interface offers a simple way to work with TensorFlow, it is sometimes not possible or convenient to use Keras. Hence, one mu... Read more

Summary:

TensorFlow is one of the most powerful frameworks made for machine learning and analysis. It's so powerful that almost all of the other machine lea... Read more

Aniket P.

Alternative software

Explorium offers a first-of-its-kind end-to-end automated external data platform for advanced analytics and machine learning. Our unique all-in-one platform automatically connects and matches internal enterprise data with thousands of relevant external data sets to accelerate your ML investment ROI and helps solve complex problems. We empower data scientists and business leaders to fuel decision-making with the right data. Check out the platform yourself at: www.explorium.ai/free-trial Learn more about Explorium

On-premise and cloud-based solution that helps build, train and deploy machine learning tools, facilitate team collaboration & more. Learn more about Azure Machine Learning

rating

4.3 ( 15 reviews )

Scientific computing framework that provides deep machine learning algorithms and uses Lua-based scripting language. Learn more about Torch

Machine learning tool that enables data mining through free online courses and big data processing. Learn more about Weka

rating

4.9 ( 10 reviews )

B2Metric is an AI-based predictive analytics solution that enables the management of customer journey analytics, risk assessment, and price optimization process within the B2Metric ML Studio platform solution. B2Metric reduces the complexities of predictive analytics projects for each size of companies. Becoming a data-driven company is such an easy task for your marketing and data teams. B2Metric AutoML solution set up an ML pipeline for the usage of marketing teams, data scientists. Learn more about B2Metric

rating

4 ( 1 reviews )

Machine learning lets users select or customize deep learning or big data processing stacks. Learn more about AISE Stacks

The Valohai platform is designed to make machine learning in production easy. Data scientists and machine learning engineers can work together to build end-to-end machine learning pipelines that take in new data, train a model, and deploy to production automatically. Everything trained on Valohai is automatically stored and versioned, so every model is always reproducible, and work is never lost. The platform is technology agnostic and ready for any cloud or on-premise setup. Learn more about Valohai

Machine learning solution that helps businesses monitor and track performances of analytical models to ensure governance Platform for MLops and Data-piplines. Serverless Kubeflow Pipelines. Learn more about AI Studio

The process involves analyzing existing processes and data, plus specialized knowledge input from experts, and paired with software-based machine learning. HALerium provides statistically sound forecasts and recommends actions based on the analysis. The entire analysis process is transparent when presented. Learn more about HALerium

A library of Nathan commands that can embed machine learning capabilities to mobile devices as well as virtual and hardware appliances. Learn more about NathanCORE