Get yourself trained on Hands-on Deep Learning with this Online Training Hands-on Deep Learning with TensorFlow.
Online Training Hands-on Deep Learning with TensorFlow
Are you short on time to start from scratch to use deep learning to solve complex problems involving topics like neural networks and reinforcement learning? If yes, then this is the course to help you. This course is designed to help you to overcome various data science problems by using efficient deep learning models built in TensorFlow.The course begins with a quick introduction to TensorFlow essentials. Next, we start with deep neural networks for different problems and then explore the applications of Convolutional Neural Networks on two real datasets. If youre facing time series problem then we will show you how to tackle it using RNN. We will also highlight how autoencoders can be used for efficient data representation. Lastly, we will take you through some of the important techniques to implement generative adversarial networks. All these modules are developed with step by step TensorFlow implementation with the help of real examples.By the end of the course you will be able to develop deep learning based solutions to any kind of problem you have, without any need to learn deep learning models from scratch, rather using tensorflow and its enormous power.About the AuthorSalil Vishnu Kapur is a Data Science Researcher at the Institute for Big Data Analytics, Dalhousie University. He is extremely passionate about Machine Learning, Deep Learning, Data mining and Big Data Analytics. Currently working as a Researcher at Deep Vision and prior to that worked as a Senior Analyst at Capgemini for around 3 years with these technologies. Prior to that Salil was an intern at IIT Bombay through the FOSSEE Python TextBook Companion Project and presently with the Department of Fisheries and Transport Canada through Dalhousie University.
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.