Introduction to Deep Learning, Keras, and TensorFlow

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This fast-paced session starts with a simple yet complete neural network, followed by an overview of activation functions, cost functions, backpropagation, and then a quick dive into CNNs.

Next, we'll create a neural network using Keras, followed by an introduction to TensorFlow and TensorBoard. For best results, familiarity with basic vectors and matrices, inner (aka "dot") products of vectors, and rudimentary Python is definitely helpful. If time permits, we'll look at the UAT, CLT, and the Fixed Point Theorem. It would be helpful if you know Zorn's Lemma, the Well-Ordering Theorem, and the Axiom of Choice.

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Meet Your Presenter:
Navin Singh holds two Graduate degrees, Master in Computer Sciences and Application and Master in Advanced Electronics. He has his undergraduate degree majoring in Mathematics and Statistics. He has been continuously working in the field of Big Data and Artificial Intelligence.

He has worked on many Implementation projects with many Fortune 100 companies like MasterCard, GE, Cisco, Brocade, Nissan and helped Government Organization like Accountant General, Counties, Health, and Human Services to achieve their financial Data management and reporting. Navin is a Marathon runner and has done his 15th Marathon. Currently, he is involved in the research on Next Generation AI and Sigma trading algorithms.

He is a hands-on technology architect with great exposure to most of the data and AI technologies. His passion is to support the next generation of engineers and data scientists and push them to achieve the highest level of excellence.

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