Building AI Using Python


  • LISP code is written in s-expressions and consists of lists
  • Prolog
  • Python

1. Lisp (programming language)
Lisp (historically, LISP) is a family of computer programming languages with a long history and a distinctive, fully parenthesized prefix notation. Originally specified in 1958, Lisp is the second-oldest high-level programming language in widespread use today. Only Fortran is older, by one year. Lisp has changed since its early days, and many dialects have existed over its history. Today, the best known general-purpose Lisp dialects are Common Lisp and Scheme.

LISP是具有悠久歷史的電腦編程語言家族,有獨特和完全括號的前綴符號表示法。起源於西元1958年,是現今第二悠久而仍廣泛使用的高階編程語言。只有FORTRAN編程語言比它更早一年。LISP編程語族已經演變出許多種方言。現代最著名的通用編程語種是 Common LispScheme

2. Prolog
Prolog is a general-purpose logic programming language associated with artificial intelligence and computational linguistics

Prolog(Programming in Logic的縮寫)是一種邏輯編程語言。它建立在邏輯學的理論基礎之上, 最初被運用於自然語言等研究領域。現在它已廣泛的應用在人工智能的研究中,它可以用來建造專家系統、自然語言理解、智能知識庫等。


1. Install Anaconda, the open source analytics platform.
2. Install NumPy, scikit-learn, iPython Notebook, and matplotlib (packages for machine learning)

Consult following books
 Python The Hard Way      [ClickHere] 
 Google Developers Python Course      [ClickHere]
 An Introduction to Python for Scientific Computing      [ClickHere]
 Learn X in Y Minutes      [ClickHere]

Anaconda (Python distribution)
Anaconda is a free and open source distribution of the Python and R programming languages for data science and machine learning related applications (large-scale data processing, predictive analytics, scientific computing), that aims to simplify package management and deployment. Package versions are managed by the package management system conda

Anaconda (Python發行版)
Anaconda 是一種 Python 語言的免費增值開源發行版 ,用於進行大規模數據處理, 預測分析, 和科學計算, 致力於簡化包的管理和部署。Anaconda 使用軟件包管理系統 Conda 進行包管理。


If you want to create artificial intelligence chatbots in Python, you’ll need AIML package (Artificial Intelligence Markup Language). First of all, create a standard startup file with on pattern. Load aiml b. Add random responses that make a dialog interesting. Now to write your own AIML file, browse for some files you already may use. For example, search among AIML files from the Alice Bot website. Enter Python.

When you create the startup file, it will then serve as a separate entity. Thus, you may have more AIML files without source code modifications. The program will start learning when there are many AIML files. Speed up the brain load. Add Python commands. So that’s an introduction to how you can make artificial intelligence using Python.