课程介绍

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

课程大纲

学习要求

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

考核标准

课件浏览100%,客观练习0%,主观练习0%,课内讨论0%。
课程内容不断迭代，成绩以当时的课程内容为准，一旦合格，可以申请证书。申请证书后，以结课处理，成绩不再改动