TensorFlow
About TensorFlow
TensorFlow is an open-source platform, which helps developers, businesses, and researchers build, launch, and manage machine learning (ML)-enabled applications using a variety of tools, built-in code libraries, and community resources. The solution offers a collection of customizable workflows to assist organizations with developing and training models using Swift, Python or JavaScript programming languages and deploying them in the cloud, on-premise or in a browser.
TensorFlow includes a JavaScripts library, which enables organizations to create new models, translate codes, and retrain existing ML models. It allows developers to create models for mobile and IoT devices using the TensorFlow Lite module. The data validation feature lets users monitor and validate volumes of data to ensure continuous operations across the ML pipeline.
Coding professionals can handle various preprocessing and dataset transformation operations such as format conversion, tokenizing and stemming of text, creating vocabularies, and normalization. TensorFlow’s model analysis functionality allows developers to determine and visualize evaluation metrics for their models to analyze performance and behavior of applications.
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- Industry: Computer Software
- Company size: 51–200 Employees
- Used Weekly for 1+ year
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- Value for Money
- Ease of Use
- Customer Support
- Likelihood to recommend 8.0 /10
Tensorflow review after 2 year of use.
Reviewed on 2021/03/09
TensorFlow helped to Learn and understand the working of any machine learning models. It is simple...
TensorFlow helped to Learn and understand the working of any machine learning models. It is simple and easy to use and is very helpful for any new comer to start their machine learning journey.
Pros
TensorFlow is easy to install and use. Machine Learning models are easy to code. Graph visualisation will help to understand the model. TensorFlow has very good community to help solve many problems and can easily learn from different tutorial videos. The cloud support is also affordable for model deployment.
Cons
Requires a lot of cpu power for model training. Visualisation of model can also be improved.
- Industry: Information Technology & Services
- Company size: 201–500 Employees
- Used for 1+ year
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Review Source
Overall rating
- Value for Money
- Ease of Use
- Customer Support
- Likelihood to recommend 9.0 /10
Most advance machine learning library
Reviewed on 2018/09/03
Building machine learning model from scratch and want full power of customisation then choose this...
Building machine learning model from scratch and want full power of customisation then choose this tool.
Pros
I think it is the most advance library for machine learning specially for deep learning. It very easy to write neural network in this library. It comes with lot of inbuilt function to process data. Also, it has lots of prebuilt function which ease the implementation of neural network.
Cons
There is no bad thing about this but initially it takes lot of time to understand it as it works on tensors instead of simple vector or array object. But once you learn this, it will be easy to write code.
- Company size: 201–500 Employees
- Used for 2+ years
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Review Source
Overall rating
- Value for Money
- Ease of Use
- Customer Support
- Likelihood to recommend 9.0 /10
Made the deep learning kids work
Reviewed on 2018/07/11
Best library for deep learning
Best library for deep learning
Pros
This library is the best for deep learning. Designing neural network with this library is very easy. Also, it compute things very fast. It has made the visualization very easy. It has lots of built in features like conv2d network, lstm etc.
Cons
It's the best thing to do stuff in deep learning but it require a long learning curve. But once you know how it works then it made your job very easy.
- Industry: Internet
- Company size: 10,000+ Employees
- Used Weekly for 1+ year
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Review Source
Overall rating
- Ease of Use
- Likelihood to recommend 9.0 /10
Deep learning is easy with TensorFlow
Reviewed on 2018/09/07
We use tensorflow LSTMs for sequence classification to mine patterns in log and customer behavior.
I...
We use tensorflow LSTMs for sequence classification to mine patterns in log and customer behavior.
In our use case, deep models decreased testing loss by 50% over a simple baseline.
Pros
Intuitive way to generate networks.
Nice visualizations with tensorboard.
Good documentation and tutorials.
Large supportive community.
Easily scaleable.
Cons
Many of the error messages can be cryptic and difficult to use when debugging.
Frequent errors caused by data type mismatches.
It is not easy to iterate quickly with Tensor flow.
TensorFlow FAQs
Below are some frequently asked questions for TensorFlow.Q. What type of pricing plans does TensorFlow offer?
TensorFlow offers the following pricing plans:
- Free Trial: Not Available
Contact TensorFlow for pricing details.
Q. Who are the typical users of TensorFlow?
TensorFlow has the following typical customers:
Self Employed, 2–10, 11–50, 51–200, 201–500, 501–1,000, 1,001–5,000
Q. What languages does TensorFlow support?
TensorFlow supports the following languages:
English
Q. Does TensorFlow support mobile devices?
TensorFlow supports the following devices:
Q. What other apps does TensorFlow integrate with?
We do not have any information about what integrations TensorFlow has
Q. What level of support does TensorFlow offer?
TensorFlow offers the following support options:
Email/Help Desk, FAQs/Forum, Knowledge Base, Phone Support
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