-- [[Main.TheodoreCwereGaelejwe][Cwere]] - 2019-03-07 ---++ Installing ROOT on Linux You can install ROOT on different platforms and but it is adviceable to run it from Linux since documentation is widely available. Detailed instructions are found on this link [[https://root.cern.ch/root/html534/guides/users-guide/InstallandBuild.html.][HowToInstallRoot]]. It is assumed that you already have Ubuntu installed but if you do not, here are some short and straightforward steps to install. *For installing on a Virtual Machine:* [[https://www.lifewire.com/install-ubuntu-linux-windows-10-steps-2202108/][ClickHere]] *For installing on your Local Machine:* [[https://tutorials.ubuntu.com/tutorial/tutorial-install-ubuntu-desktop/][ClickHere]] *Notes:* * The link provided for installing on VM refers to an old version of Ubuntu but the process is the same for most versions. * Remember to install Guest Additions as they come with features that assist with display and audio. Make sure the Additions are compatible with your version of Ubuntu. ---++ Accessing ROOT on lxplus Another way to access ROOT is through *LXPLUS*. [[http://information-technology.web.cern.ch/services/lxplus-service/][LXPLUS]] is a cluster used for executing jobs that would otherwise take eons to run on your local machine. It is accessed by using the _ssh_ command with your CERN username. The link provided has more details about the cluster. ---++ Getting Started with Tensorflow Tensorflow is a powerful tool for deep learning tasks in machine learning. The use of deep neural networks has gained popularity and justification in the HEP community of late. A number of researchers indicate that DNNs do better than the trusted BDT algorithm in HEP data analysis, however, this is yet to be rigorously tested. See the following for examples [[http://pprc.qmul.ac.uk/~charman/synapse-report.pdf/][1]] [[https://www.nature.com/articles/ncomms5308/][2]]. The jupyter notebook below has step by step implementation of a basic DNN on HEP data. * [[%ATTACHURL%/DNN_on_Tensorflow.ipynb][DNN_on_Tensorflow.ipynb]]: DNN_on_Tensorflow.ipynb</verbatim>
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