LEARNING PATH: TensorFlow: Complete Solutions to TensorFlow | Data Science Online Course by Udemy

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Perform efficient deep learning on images, text, and data using TensorFlow

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LEARNING PATH: TensorFlow: Complete Solutions to TensorFlow

TensorFlow has quickly become a popular choice of tool for performing fast, efficient, and accurate deep learning. This Learning Path presents the implementation of practical, real-world projects, teaching you how to leverage TensorFlows capabilities to perform efficient deep learning. So, if you are interested to acquire complete knowledge on deep learning with TensorFlow, then you should surely go for this Learning Path. Packts Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. The highlights of this Learning Path are: Learn to process text for natural language understanding Use recommenders to predict word similarity Create a machine learning model for sentence generation Let’s take a look at your learning journey. To start with, you will be acquainted with the different paradigms of performing deep learning such as deep neural nets, convolutional neural networks, recurrent neural networks, and more, and how they can be implemented using TensorFlow. You will also be demonstrated with the help of end-to-end implementations of three real-world projects on popular topic areas such as natural language processing, image classification, fraud detection, and much more. Next, you will focus on the most plentiful source of text out there, that is, email. You will build up a label predictor, similar in effect to the technology Google uses to power the social and promotions tabs. Therefore, you will be able to build your own email classification and automated workflow hooks. Next, you will work with categorical data to predict loan performance. You will use this technique and can effectively predict performance or detect potential fraud. You will also work with recurrent neural networks, which generate realistic test and placeholder data. By the end of this Learning Path, you will have mastered deep learning with Tensorflow through interesting use cases to ensure a quality learning experience. Meet Your Expert: We have the best works of the following esteemed authors to ensure that your learning journey is smooth: Will Ballard serves as chief technology officer at GLG and is responsible for the engineering and IT organizations. Prior to joining GLG, Will was the executive vice president of technology and engineering at Demand Media. Before that, he was vice president and chief technology officer at Pluck, through its acquisition by Demand Media. At both organizations Will managed large teams of engineers responsible for software architecture, design, development, and quality assurance. He was also responsible for the design and operation of large data centers that helped run site services for customers including Gannett, Hearst Magazines, NFL.com, NPR, The Washington Post, and Whole Foods. Will has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works.com (now Bank of America). Will graduated Magna Cum Laude with a BS in Mathematics from Claremont McKenna College.

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