Tensorflow Deep Learning Solutions for Images. With the help of this course you can Use Tensorflow’s capabilities to perform efficient deep learning on Images.
This course was created by Packt Publishing. It was rated 4.1 out of 5 by approx 10622 ratings. There are approx 83830 users enrolled with this course, so don’t wait to download yours now. This course also includes 1.5 hours on-demand video, 1 Supplemental Resource, Full lifetime access, Access on mobile and TV & Certificate of Completion.
What Will You Learn?
Set up a Machine Learning environment
Work with Docker and Keras
Process images for machine vision
Process text for Natural language understanding
Work with tabular data to make financial predictions
Generate synthetic test data with machine learning
Tensorflow is Google’s popular offering for machine learning and deep learning. It has quickly become a popular choice of tool for performing fast, efficient, and accurate deep learning. This course presents the implementation of practical, real-world projects, teaching you how to leverage Tensforflow’s capabilties to perform efficient deep learning.
In this video, 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.
This will 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 more. By the end of this course, you will have mastered all the concepts of deep learning and their implementation with Tensorflow and Keras.
About The Author
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 of 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.