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Open Source Software Library for Machine Intelligence
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What is TensorFlow?

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
TensorFlow is a tool in the Machine Learning Tools category of a tech stack.
TensorFlow is an open source tool with 150.8K GitHub stars and 83.3K GitHub forks. Here’s a link to TensorFlow's open source repository on GitHub

Who uses TensorFlow?

370 companies reportedly use TensorFlow in their tech stacks, including Uber, Delivery Hero, and Ruangguru.

1741 developers on StackShare have stated that they use TensorFlow.

TensorFlow Integrations

JavaScript, Jupyter, Keras, Databricks, and Kubeflow are some of the popular tools that integrate with TensorFlow. Here's a list of all 43 tools that integrate with TensorFlow.
Public Decisions about TensorFlow

Here are some stack decisions, common use cases and reviews by companies and developers who chose TensorFlow in their tech stack.

I am going to send my website to a Venture Capitalist for inspection. If I succeed, I will get funding for my StartUp! This website is based on Django and Uses Keras and TensorFlow model to predict medical imaging. Should I use Heroku or PythonAnywhere to deploy my website ?? Best Regards, Adarsh.

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Shared insights

Hello All, I have concerns about which framework to use in my case. I'm working on a project that uses TensorFlow for implementing CNN and image processing, it also deals with a huge dataset. Shall I implement the rest APIs in Phalcon because of its speed and great performance or Falcon since I'm working with TensorFlow and doing image processing steps?

PS: APIs are to receive the image from the user, and call *.py files to execute image processing steps and CNN Thanks In Advance :D

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Blog Posts

TensorFlow Alternatives & Comparisons

What are some alternatives to TensorFlow?
Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
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TensorFlow's Followers
2281 developers follow TensorFlow to keep up with related blogs and decisions.