Chapter 1 Course Guidance in
this chapter is only one, and only one purpose, is to tell you why you want to learn this course, this course will teach you what, what pre-knowledge required before school.
Chapter 2 Introduction to machine learning and neural networks
in this chapter will use the medieval man feet long, SIRI voice recognition, blind date, a large number of vivid examples to explain the theoretical knowledge of machine learning and neural networks.
Chapter 3 Tensorflow.js About
Tensorflow.js is the core framework of this course, you are familiar with this chapter to help combat it in front of the hands of the "weapons", will involve introduction Tensorflow.js, installation methods, and what is Tensor? Why use Tensor and other knowledge
Chapter 4 Linear regression
of this chapter will take you to develop and train your life first neural network model, though it is only the starting point of a neuron, but it is the way your machine learning!
Chapter 5 normalized
Jiujiuguiyi ......, and so on, we are not in the abacus, but in the alchemy (training model)! This chapter will be to predict the height and weight as an example to explain this alchemy normalization of best practice.
Chapter 6 logistic regression
of the mission is to develop a neural network to two types of points on the plane, make a clean break!
Chapter 7 multilayer neural network
life is not so much a clean break of simple questions to complex problems, we can develop a multilayer neural network model with the activation function, bend angles and waving his hand, "knife" to cut!
Chapter 8 multi-classification
in this chapter will be to Iris classification, for example, learning to use softmax and two cross-entropy algorithm to make multi-classification neural network
Chapter 9 underfitting and over-fitting
and to learn best practices alchemy of time up! Completion of this mission, you just glance at the training image, you can determine it is less fit or too fitted.
Chapter 10 convolutional neural network (CNN) recognize handwritten numbers
in this chapter will first use a lot of animation theory to explain convolution neural network, and then use it to build and train JS! Start building a life of deep learning model now!
Chapter 11. Using pre-trained classification models pictures
to other people trained convolution neural network model directly for use! Ism also need to learn Oh!
Chapter 12 based on the image transfer learning classifier: Trademark Recognition
of this chapter will be to identify the trademark, for example, explain how to transfer learning to use more efficiently the picture classification, finished this chapter, you can develop Zhaomaohuahu Draw Something, flowers classification, waste, Emoji hunters and other games and applications up!
Chapter 13 pre-trained model using voice recognition
for voice recognition in your browser.
Chapter 14 based transfer learning speech recognizers: Voice Carousel Figure
chapter will take you can develop a carousel view of a remote voice-activated, the end of this chapter, you can develop your own simple version of the voice assistant SIRI!
Chapter 15 Python and JavaScript model system conversion
in this chapter are learning practical work in the most common technique: the Python model into JS model, can be deployed to the browser. JS model of fragmentation, compression, acceleration and other conversion optimization is essential to work Oh!
Chapter 16 Lessons Learned
on the overall curriculum review.
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