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Data Miner
Data Miner

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What is Data Miner?

It is a Google Chrome extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet.

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.
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Why do developers choose Data Miner?
Why do developers choose TensorFlow?
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      What are some alternatives to Data Miner and TensorFlow?
      Pandas
      Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
      NumPy
      Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
      Anaconda
      A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
      SciPy
      Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
      Pentaho Data Integration
      It enable users to ingest, blend, cleanse and prepare diverse data from any source. With visual tools to eliminate coding and complexity, It puts the best quality data at the fingertips of IT and the business.
      See all alternatives
      Decisions about Data Miner and TensorFlow
      Conor Myhrvold
      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 434.9K views
      atUber TechnologiesUber Technologies
      PyTorch
      PyTorch
      Keras
      Keras
      TensorFlow
      TensorFlow

      Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

      At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

      TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details鈥攆or instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA鈥檚 CUDA toolkit.

      Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo鈥檚 deep learning toolkit which makes it easier to start鈥攁nd speed up鈥攄istributed deep learning projects with TensorFlow:

      https://eng.uber.com/horovod/

      (Direct GitHub repo: https://github.com/uber/horovod)

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      How developers use Data Miner and TensorFlow
      Avatar of Eliana Abraham
      Eliana Abraham uses TensorFlowTensorFlow

      Machine Learning in EECS 445

      Avatar of Taylor Host
      Taylor Host uses TensorFlowTensorFlow

      Pilot integration for retraining.

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