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      • Even though the neural network framework we used itself only works in a single-node, we can use Spark to distribute the hyperparameter tuning process and model deployment. This not only cuts down the training time but also improves accuracy and gives us a better understanding of various hyperparameters’ sensibility.
      www.databricks.com/blog/2016/01/25/deep-learning-with-apache-spark-and-tensorflow.html

      Deep Learning with Apache Spark and TensorFlow - Databricks

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  3. towardsdatascience.com › deep-learning-with-apacheDeep Learning With Apache Spark — Part 1 | by Favio Vázquez ...

    Apr 9, 2018 · Why would you want to do Deep Learning on Apache Spark? This was the question I asked myself before beginning to study the subject. And the answer comes in two parts for me: Apache Spark is an amazing framework for distributing computations in a cluster in a easy and declarative way.

    • Favio Vázquez

  4. www.databricks.com › blog › 2016/01/25Deep Learning with Apache Spark and TensorFlow - Databricks

    Jan 25, 2016 · You might be wondering: what’s Apache Spark’s use here when most high-performance deep learning implementations are single-node only? To answer this question, we walk through two use cases and explain how you can use Spark and a cluster of machines to improve deep learning pipelines with TensorFlow:

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  6. www.analyticsvidhya.com › blog › 2022An End-to-end Guide on ML Pipeline Using Apache Spark in Python

    May 3, 2022 · In this article, we will build a machine learning pipeline using spark. We will create a Car price predictor using apache spark in python.

  7. www.kdnuggets.com › 2018 › 04Deep Learning With Apache Spark: Part 1 - KDnuggets

    Deep Learning Pipelines is an open source library created by Databricks that provides high-level APIs for scalable deep learning in Python with Apache Spark. It is an awesome effort and it won’t be long until is merged into the official API, so is worth taking a look of it.

  8. www.infoworld.com › article › 2243822Why you should use Spark for machine learning - InfoWorld

    Feb 11, 2016 · Spark enhances machine learning because data scientists can focus on the data problems they really care about while transparently leveraging the speed, ease, and integration of Spark’s...

  9. www.datacamp.com › tutorial › apache-spark-tutorialApache Spark Tutorial: Machine Learning - DataCamp

    Jul 28, 2017 · Apache Spark and Python for Big Data and Machine Learning. Apache Spark is known as a fast, easy-to-use and general engine for big data processing that has built-in modules for streaming, SQL, Machine Learning (ML) and graph processing.

  10. towardsdatascience.com › the-what-why-and-when-ofThe What, Why, and When of Apache Spark | by Allison Stafford ...

    Jan 12, 2020 · If you are already using a supported language (Java, Python, Scala, R) Spark makes working with distributed data (Amazon S3, MapR XD, Hadoop HDFS) or NoSQL databases (MapR Database, Apache HBase, Apache Cassandra, MongoDB) seamless.

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