• ONLINE WEBINAR: Image Classification Done Simply Using Keras and TensorFlow

    *Please register HERE (https://goo.gl/IIaqKP)to get the unique link to join the webinar* Are you willing to learn how to build an image classifier using Keras with a TensorFlow backend? Join the webinar (https://goo.gl/IIaqKP) to learn more! Overview The fact that computers can see is just not that amazing anymore. But, the techniques for teaching a computer to do this are now simpler and more refined than ever. In this webinar, Rajiv Shah (https://www.linkedin.com/in/rcshah?authType=NAME_SEARCH&authToken=TVD5&locale=en_US&srchid=854662381470146485173&srchindex=1&srchtotal=1&trk=vsrp_people_res_name&trkInfo=VSRPsearchId%3A854662381470146485173%2CVSRPtargetId%3A15452467%2CVSRPcmpt%3Aprimary%2CVSRPnm%3Atrue%2CauthType%3ANAME_SEARCH) will describe the process of building an image classifier using Keras with a TensorFlow backend and discuss how to extend the code to your own pictures to make a custom image classifier. The approach here uses Keras, which is emerging as the best library for building neural networks. The code here also assumes you are using TensorFlow as the underlying library. The presentation will give a basic understanding of image classification and show the techniques used in industry to build image classifiers. You will learn: - How to build a simple convolutional network - How to augment the data - How to use a pretrained network - How to use transfer learning by modifying the last few layers of a pretrained network The classification will be based on the classic example of classifying cats and dogs. The code for the presentation can be found here (https://github.com/rajshah4/image_keras). About the Presenter: Rajiv Shah (https://www.linkedin.com/in/rcshah/) is a senior data scientist at Caterpillar and an Adjunct Assistant Professor at the University of Illinois at Chicago. Rajiv is an active member of the data science community in Chicago with an interest into public policy issues, such as surveillance in Chicago. He has a PhD from the University of Illinois at Urbana Champaign. You find more of his projects at www.rajivshah.com (https://rajivshah.com/).

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  • LIVE WEBINAR: Deep Learning for Cyber Security

    *Please register HERE (https://goo.gl/tIiJwX) to get the unique link to join the webinar* Are you willing to learn about Deep Learning for Cyber Security? Join the webinar (https://goo.gl/tIiJwX) to learn more! In this webinar, Steven Hutt (https://www.linkedin.com/in/huttsteven/), Consultant in Deep Learning and Financial Risk, will provide an overview of network anomaly detection. Agenda: - Searching for anomalous network flows is a challenging task due to the wide statistical variety of network behavior - Overview of past applications of Machine Learning to network anomaly detection - The advantages and challenges of a Deep Learning approach - Handling categorical data in Deep Learning - Q&A session Who should attend: This webinar will be of interest to Data Scientists, Software Engineers and Entrepreneurs in the areas of Connected Cars, Internet of Things/Industrial Internet, Medical Devices, Financial Technology (blockchain) and predictive apps/APIs of all sorts. About the presenter: Steven Hutt (https://www.linkedin.com/in/huttsteven/) is a consultant in Deep Learning and Financial Risk, currently working in Cyber Security and Algorithmic Trading. He has previously been head quant for credit at UBS and Morgan Stanley, and before that a mathematician doing stuff in an obscure branch of topology.

  • ONLINE WEBINAR: Deep Learning Using TensorFlow and TensorFlow-Slim

    *****************WAITLIST ONLY******************* *******PLEASE REGISTER HERE (http://paas.ly/2fCxUf8)****** Do you want learn how CNNs work and how to build and train such networks? Join the webinar (http://paas.ly/2fCxUf8) to learn more! In this webinar, Dipendra Jha (https://www.linkedin.com/in/dipendra009?authType=OUT_OF_NETWORK&authToken=k4Fx&locale=en_US&srchid=854662381478188385692&srchindex=1&srchtotal=2413&trk=vsrp_people_res_name&trkInfo=VSRPsearchId%3A854662381478188385692%2CVSRPtargetId%3A194620481%2CVSRPcmpt%3Aprimary%2CVSRPnm%3Atrue%2CauthType%3AOUT_OF_NETWORK), Ph.D. student in Computer Science from Northwestern University, will provide a brief introduction to Deep Learning and TensorFlow, followed by actual implementation and demonstration of MNIST image classification using convolutional neural networks (CNNs). Agenda: Introduction to the Fundamentals of Deep LearningThe Strengths of Using TensorFlowImage Classification Using CNNs for MNIST DatasetHow CNNs work and How to Build and Train Such NetworksThe Usage of TensorFlow for large-scale application of Deep Learning to Big Datasets in IndustryQ&A Join the webinar to (http://www.altoros.com/blog/event/deep-learning-using-tensorflow-and-tensorflow-slim/#get_record): Learn more about the fundamentals of deep learning, followed by the strengths of using TensorFlow Look about image classification using CNNs for MNIST datasetDiscover how CNNs work and how to build and train such networks Examine how TensorFlow can be used for large-scale application of deep learning to big datasets in industry Who should attend: This webinar will be of interest to Data Scientists, Software Engineers and Entrepreneurs in the areas of Connected Cars, Internet of Things/Industrial Internet, Medical Devices, Financial Technology (blockchain) and predictive apps/APIs of all sorts. About the presenter: Dipendra Jha (https://www.linkedin.com/in/dipendra009?authType=OUT_OF_NETWORK&authToken=k4Fx&locale=en_US&srchid=854662381478188385692&srchindex=1&srchtotal=2413&trk=vsrp_people_res_name&trkInfo=VSRPsearchId%3A854662381478188385692%2CVSRPtargetId%3A194620481%2CVSRPcmpt%3Aprimary%2CVSRPnm%3Atrue%2CauthType%3AOUT_OF_NETWORK) is is a fourth-year Ph.D. student in Computer Science from Northwestern University. He is exploring the field of Deep Learning and Machine Learning using High Performance Computing (HPC) systems in the CUCIS lab under Prof. Alok Choudhary. His research focuses on scaling up deep learning and machine learning models using HPC (CPU and GPU) clusters, and their application to Material Science and Social Media Analytics. Before this, he completed his Master’s in Computer Science from Northwestern University. He worked in the field of Computer Networks, Distributed Systems and Cellular Networks in Aqualab under Prof. Fabian Bustamante. During this period, his research spanned from Web Page Performance Optimizations, Network Measurements and Community WiFi to Inter-domain Routing in Cellular Networks, IXPs and Content Distribution Networks (CDNs). He completed his Bachelors’ in Computer Engineering from Tribhuvan University in Nepal.