Intel AI Academy – Applied Deep Learning with Tensorflow

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TensorFlow* is a popular machine learning framework and open-source library for dataflow programming. In this course, you will learn about:

  • The fundamentals of building models with TensorFlow*
  • Machine learning basics like linear regression, loss functions, and gradient descent
  • Important techniques like normalization, regularization, and mini-batching
  • Kernels and how to apply them to convolutional neural networks (CNN)
  • The basic template for a CNN and different parameters that can be adjusted
  • TFRecord, queues, and coordinators

By the end of this course, students will have a firm understanding of:

  • Basic network construction, kernels, pooling, and multiclass classification
  • How to expand a basic network into a more complex network
  • Using transfer learning to take advantage of existing networks by building on top of them

The course is structured around eight weeks of lectures and exercises. Each week requires at least three hours to complete.

Prior Knowledge

Before You Begin