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Author: misamaliraza94

  • H2O – Flow

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    In the last lesson, you learned to create H2O based ML models using command line interface. H2O Flow fulfils the same purpose, but with a web-based interface. In the following lessons, I will show you how to start H2O Flow and to run a sample application. Starting H2O Flow The H2O installation that you downloaded…

  • Installation

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    H2O can be configured and used with five different options as listed below −H2O – InstallationH2O can be configured and used with five different options as listed below − In our subsequent sections, you will see the instructions for installation of H2O based on the options available. You are likely to use one of the…

  • Introduction

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    Have you ever been asked to develop a Machine Learning model on a huge database? Typically, the customer will provide you the database and ask you to make certain predictions such as who will be the potential buyers; if there can be an early detection of fraudulent cases, etc. To answer these questions, your task…

  • H2O Tutorial

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    H2O is an open source Machine Learning framework with full-tested implementations of several widely-accepted ML algorithms. You just have to pick up the algorithm from its huge repository and apply it to your dataset. It contains the most widely used statistical and ML algorithms. H2O provides an easy-to-use open source platform for applying different ML…

  • Problem

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    We assure you that you will not find any difficulty in this tutorial. In case you come up with a query, or you find any mistake in this tutorial, do let us know by posting it in the contact form so that we can further improve it.

  • Disadvantages of Keras

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    Prerequisite This Keras tutorial is made for both beginners and professionals, to help them understand the fundamental concept of Keras. After the completion of this tutorial, you will find yourself at a moderate level of expertise from where you can take yourself to the next level. Audience Since Keras is a deep learning’s high-level library,…

  • Advantages of Keras

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    Keras encompasses the following advantages, which are as follows:

  • How Keras support the claim of being multi-backend and multi-platform?

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    Keras can be developed in R as well as Python, such that the code can be run with TensorFlow, Theano, CNTK, or MXNet as per the requirement. Keras can be run on CPU, NVIDIA GPU, AMD GPU, TPU, etc. It ensures that producing models with Keras is really simple as it totally supports to run…

  • Keras user experience

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  • What makes Keras special?

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