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Tensorflow Deep Learning Solutions for Images [Video]

More Information
  • 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.

Style and Approach

This course takes a step-by-step approach, helping you explore all the functioning of TensorFlow.

  • Build practical, real-world deep learning projects in Tensorflow
  • Master the different deep learning paradigms and build real-world projects related to Computer Vision, Natural Language Understanding, and deep learning
  • Your handy tutorial to mastering deep learning with Tensorflow through interesting use cases to ensure a quality learning experience
Course Length 1 hour 25 minutes
Date Of Publication 9 Oct 2017


Will Ballard

Will Ballard is the chief technology officer at GLG, responsible for engineering and IT. 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, NPR, The Washington Post, and Whole Foods. He has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works (now Bank of America).