Installation

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… Continue reading Installation

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Introduction

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… Continue reading Introduction

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H2O Tutorial

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… Continue reading H2O Tutorial

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Problem

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.

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Categorized as 3. Keras

Disadvantages of Keras

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,… Continue reading Disadvantages of Keras

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Keras Tutorial

Keras is an open-source high-level Neural Network library, which is written in Python is capable enough to run on Theano, TensorFlow, or CNTK. It was developed by one of the Google engineers, Francois Chollet. It is made user-friendly, extensible, and modular for facilitating faster experimentation with deep neural networks. It not only supports Convolutional Networks… Continue reading Keras Tutorial

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