Text Generation with Markov Chains in Python

提供方
Coursera Project Network
在此指导 项目中,您将:

l​earn about Markov chains and apply this concept to modeling and generating text.

Clock1 hour
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

In this project-based course, you will learn about Markov chains and use them to build a probabilistic model of an entire book’s text. This will be done from first principles, without libraries. Markov chains are a simple but fundamental approach to modeling stochastic processes, with many practical applications. By the end of this project, you will have generated a random new text based on the book you modeled, using code you wrote in Python.

您要培养的技能

Artificial Intelligence (AI)Probability TheoryPython ProgrammingNumpyMarkov Chain

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Read text from file

  2. Build a transition probability matrix

  3. Generate text using a Markov chain

  4. Improve capitalization, punctuation and spacing

  5. Improve text generation with k-token Markov chains

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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