Programming

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P1: TensorFlow Basics

    • Goal: Understand what TensorFlow is, and install the TensorFlow 1.x.

    • Readings:

    • Install TensorFlow 1.x on your computer.

      • You can install it on Linux, Mac OS, or Windows.

      • You can choose to install CPU or GPU versions of TensorFlow.

    • There are two things you have to write in this report page

      • Installation steps and practice codes (screen capture)

      • Bug/difficulty you encounter, and the way you solve it.

P2: TensorFlow Basics II

    • Goal: Understand TensorFlow basic syntax, such as session, variable, placeholder.

    • Readings: Tensorflow tutorials 神经网络教学教程，周莫烦，Youtube影片之7-12部。

    • Report page: There are three things you have to write in this report page

      • Execute all the sample codes in the 6 tutorial videos. Show and explain those sample codes.

      • Bug/difficulty you encounter, and the way you solve it.

      • Refer at least 5 web pages/books/materials for your learning of tensorflow in this homework. The book/youtube videos provided by the teacher can not be referred in your homework.

P3: Doing Math with TensorFlow

  • Goal: tensor data structure, fractals, gradients, random number generation, and partial differential equation.

  • Readings

    • "Chapter 2 Doing Math with TensorFlow", Getting Started with TensorFlow, G. Zaccone, Packt, 2016. 中文譯本：「第二章 用TensorFlow求解數學問題」，深度學習快速入門─使用TensorFlow，G. Zaccone著/傅運文譯，博碩文化，2017。

  • Report page: There are three things you have to write in this report page

      • Execute all the sample codes in the chapter. Show and explain those sample codes. Some extension and/or modification of the sample codes are welcome.

      • Bug/difficulty you encounter, and the way you solve it.

      • Refer at least 5 web pages/books/materials for your learning of tensorflow in this homework. The book/youtube videos provided by the teacher can not be referred in your homework.

P4: Starting with Machine Learning

  • Goal: Implementation of linear regression, classifier(kNN for MNIST), k-means clustering.

  • Readings

    • "Chapter 3 Starting with Machine Learning", Getting Started with TensorFlow, G. Zaccone, Packt, 2016. 中文譯本：「第三章 機器學習簡介與應用」，深度學習快速入門─使用TensorFlow，G. Zaccone著/傅運文譯，博碩文化，2017。

  • References

  • Report page: There are three things you have to write in this report page

      • Execute all the sample codes in the chapter. Show and explain those sample codes. Some extension and/or modification of the sample codes are welcome.

      • Bug/difficulty you encounter, and the way you solve it.

      • Refer at least 5 web pages/books/materials for your learning of tensorflow in this homework. The book/youtube videos provided by the teacher can not be referred in your homework.

  • Option: TensorFlow SVM implementation for MNIST

    • Apply both Linear SVM and Kernel SVM for MNIST.

    • Please find SVM sample codes from: TensorFlow Course and Tutorial codes, GitHub. You can also find TensorFlow SVM code by yourself. However, you have to provide the references of your referred codes.

P5: Introducing Neural Networks

P6: Deep Learning