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AI with Pythonli

AI with PythonAbout the TutorialArtificial intelligence is the intelligence demonstrated by machines, in contrast to theintelligence displayed by humans.This tutorial covers the basic concepts of various fields of artificial intelligence like ArtificialNeural Networks, Natural Language Processing, Machine Learning, Deep Learning, Geneticalgorithms etc., and its implementation in Python.AudienceThis tutorial will be useful for graduates, post graduates, and research students who eitherhave an interest in this subject or have this subject as a part of their curriculum. Thereader can be a beginner or an advanced learner.PrerequisitesWe assume that the reader has basic knowledge about Artificial Intelligence and Pythonprogramming. He/she should be aware about basic terminologies used in AI along withsome useful python packages like nltk, OpenCV, pandas, OpenAI Gym, etc.Copyright & Disclaimer Copyright 2016 by Tutorials Point (I) Pvt. Ltd.All the content and graphics published in this e-book are the property of Tutorials Point (I)Pvt. Ltd. The user of this e-book is prohibited to reuse, retain, copy, distribute or republishany contents or a part of contents of this e-book in any manner without written consentof the publisher.We strive to update the contents of our website and tutorials as timely and as precisely aspossible, however, the contents may contain inaccuracies or errors. Tutorials Point (I) Pvt.Ltd. provides no guarantee regarding the accuracy, timeliness or completeness of ourwebsite or its contents including this tutorial. If you discover any errors on our website orin this tutorial, please notify us at contact@tutorialspoint.comi

AI with PythonTable of ContentsAbout the Tutorial . iAudience . iPrerequisites . iCopyright & Disclaimer . iTable of Contents . ii1.AI with Python – Primer Concepts. 1Basic Concept of Artificial Intelligence (AI) . 1The Necessity of Learning AI . 1What is Intelligence? . 2What is Intelligence Composed Of? . 3Learning l . 4What’s Involved in AI . 6Application of AI . 6Cognitive Modeling: Simulating Human Thinking Procedure . 7Agent & Environment . 82.AI with Python – Getting Started . 9Why Python for AI . 9Features of Python . 9Installing Python . 10Setting up PATH . 11Running Python . 12Script from the Command-line . 13Integrated Development Environment . 133.AI with Python – Machine Learning . 15Types of Machine Learning (ML) . 15Most Common Machine Learning Algorithms . 16ii

AI with Python4.AI with Python – Data Preparation . 20Preprocessing the Data . 20Techniques for Data Preprocessing . 21Labeling the Data . 235.AI with Python – Supervised Learning: Classification . 26Steps for Building a Classifier in Python . 26Building Classifier in Python . 29Logistic Regression . 34Decision Tree Classifier . 37Random Forest Classifier . 39Performance of a classifier . 40Class Imbalance Problem . 42Ensemble Techniques . 436.AI with Python – Supervised Learning: Regression . 44Building Regressors in Python . 447.AI with Python – Logic Programming . 49How to Solve Problems with Logic Programming. 49Installing Useful Packages . 50Examples of Logic Programming . 50Checking for Prime Numbers . 51Solving Puzzles . 528.AI with Python – Unsupervised Learning: Clustering . 55What is Clustering? . 55Algorithms for Clustering the Data . 55Measuring the Clustering Performance . 61Calculating Silhouette Score . 61Finding Nearest Neighbors . 63K-Nearest Neighbors Classifier . 65iii

AI with Python9.AI with Python – Natural Language Processing . 69Components of NLP . 69Difficulties in NLU . 69NLP Terminology . 70Steps in NLP . 7010. AI with Python – NLTK package . 72Importing NLTK . 72Downloading NLTK’s Data . 72Installing Other Necessary Packages . 73Concept of Tokenization, Stemming, and Lemmatization . 73Chunking: Dividing Data into Chunks . 75Types of chunking . 76Bag of Word (BoW) Model . 77Concept of the Statistics . 78Building a Bag of Words Model in NLTK . 79Solving Problems . 79Topic Modeling: Identifying Patterns in Text Data . 84Algorithms for Topic Modeling . 8411. AI with Python – Analyzing Time Series Data . 86Introduction . 86Installing Useful Packages . 86Pandas: Handling, Slicing and Extracting Statistic from Time Series Data . 87Extracting Statistic from Time Series Data . 91Analyzing Sequential Data by Hidden Markov Model (HMM). 95Example: Analysis of Stock Market data. 9612. AI with Python – Speech Recognition . 99Building a Speech Recognizer .

AI with Python i About the Tutorial Artificial intelligence is the intelligence demonstrated by machines, in contrast to the intelligence displayed by humans.

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