Machine Learning Workshop

Hi All, I am excited to invite you for a Machine Learning Workshop. All levels from complete novices to experienced data scientists/engineers/analysts/enthusiasts are welcome at the meetup. The best way to learn is to practice and share the knowledge. We recommend to bring a fully charged laptop with programming environment installed (i.e. Python and/or R) and ready to use. Agenda: 9:30 – 9:45 Networking, brainstorming ideas for the next events9:45 – 10:15 Machine Learning Web Services and Visualisation by Severino10:15 – 10:45 Machine Learning with R by Eoghan10:45 – 11:00 Coffee Break and networking11:00 – 11:30 Host based Intrusion Detection system using Deep Neural Networks by Ashima11:15 – 12:45 Coding time – split into groups and work on the DS/ML/DE project or kaggle competition Machine Learning Web Services and Visualisation -Part 1We will explore an alternative to the Jupyter Kernel Gateway for turning a machine learning algorithm into a web service. A Jupyter Notebook can be used to develop machine learning models that can dynamically interact with an API endpoint, thereby providing interaction to users. -Part 2Pandas python module represents a valuable tool for Data Scientists, however, Dataframes cannot be easily visualised with existing Javascript graphical libraries. As a use case, I will show how to refactor open source code to support interactive visualisation of Dataframes in a web-page. Severino Tessarin is a creative programmer with years of experience in several programming languages for applications related to information technology, science and engineering. Machine Learning with R In this tutorial we will use supervised & unsupervised machine learning to tackle two different types of problem.Firstly, we will make predictions using linear regression.Secondly, we will make classifications using decision trees and KNN. Requirements: R & R Studio. The data sets will be downloaded from the web and the scripts will be available from a Github repo.We will collectively execute the scripts on the chosen data line by line. Eoghan Hynes: Post graduate software researcher in A.I.T. Involved in user QoE of imerrsive technologies. Host based Intrusion Detection system using Deep Neural Networks To develop a computationally efficient Anomaly host based intrusion detection system using stacked CNN and RNN with reduced training times. Ashima Chawla Post graduate software researcher in A.I.T. Let Roman Golovnya know if you keen to present at this or future events at Data Science and Engineering Club. You can contact via meetup messages or email [masked]. Looking forward to seeing you there!