Text Generation with Markov Chains in Python

提供方
Coursera Project Network
在此指導項目中,您將:

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

Clock1 hour
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

  • Artificial Intelligence (AI)
  • Probability Theory
  • Python Programming
  • Numpy
  • Markov Chain

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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常見問題

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