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TensorFlow

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 160K GitHub stars and 85.7K GitHub forks. Here’s a link to TensorFlow's open source repository on GitHub

Who uses TensorFlow?

Companies
443 companies reportedly use TensorFlow in their tech stacks, including Uber, Delivery Hero, and Hepsiburada.

Developers
2122 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 46 tools that integrate with TensorFlow.
Pros of TensorFlow
25
High Performance
16
Connect Research and Production
13
Deep Flexibility
9
Auto-Differentiation
9
True Portability
2
Easy to use
2
High level abstraction
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Powerful
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
on
Falcon
Phalcon
TensorFlow

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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Zack Shainsky
Field Data Scientists at Zepl · | 6 upvotes · 8.7K views
Shared insights
on
TensorFlow

I am working on a data collection project which requires processing images of playing cards for a deck-building game called StarRealms (https://www.starrealms.com/). I need to be able to read in a database of images or videos and recognize each card as a game is played. I believe this would involve some computer vision for image recognition and TensorFlow modeling to ensure an accurate prediction. Which technology stack would be the best for this job? Thank you for the help!

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Aicha Mahfoudh
Shared insights
on
Tesseract OCR
TensorFlow

Can I use both TensorFlow and Tesseract OCR to create a model that detects text out of a document pdf

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rashid munir
freelancer at freelancer · | 3 upvotes · 17.3K views

Need your kind suggestion if I should choose TensorFlow.js or TensorFlow with Python for ML models. As I don't want to go and have not gone too deep in JavaScript, I need your suggestion.

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Blog Posts

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Pinterest

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Jobs that mention TensorFlow as a desired skillset

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TensorFlow Alternatives & Comparisons

What are some alternatives to TensorFlow?
Theano
Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).
PyTorch
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
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.
Keras
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.
See all alternatives

TensorFlow's Followers
2841 developers follow TensorFlow to keep up with related blogs and decisions.