Learn AI with Python

(AI-PYTHON.AW1) / ISBN : 978-1-64459-677-7
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About This Course

Skills You’ll Get

1

Preface

2

Introduction to AI and Python

  • Introduction
  • Introduction to Artificial Intelligence (AI)
  • Why to learn AI?
  • Understanding intelligence
  • Various fields of study in AI
  • Applications of AI in various industries
  • How does artificial intelligence learn?
  • AI agents and environments
  • AI and Python – how do they relate?
  • Python3 - installation and setup
  • Conclusion
  • Questions
3

Machine Learning and Its Algorithms

  • Introduction
  • Understanding Machine Learning (ML)
  • The Landscape of Machine Learning Algorithms
  • Components of a Machine Learning algorithm
  • Different learning styles in machine learning algorithms
  • Popular machine learning algorithms
  • Questions
4

Classification and Regression Using Supervised Learning

  • Introduction
  • Classification
  • Various steps to build a classifier using Python
  • Lazy learning versus eager learning
  • Performance metrics for classification
  • Regression
  • Various steps to build a regressor using Python
  • Performance metrics for regression
  • Conclusion
  • Questions
5

Clustering Using Unsupervised Learning

  • Introduction
  • Clustering
  • Various methods to form clusters
  • Important ML clustering algorithms
  • Conclusion
  • Questions
6

Solving Problems with Logic Programming

  • Introduction
  • Logic programming
  • Building blocks of logic programming
  • Useful Python packages for logic programming
  • Implementation examples
  • Conclusion
  • Questions
7

Natural Language Processing with Python

  • Introduction
  • Natural Language Processing (NLP)
  • Installing Python's NLTK Package
  • Understanding tokenization, stemming, and lemmatization
  • Understanding chunking
  • Understanding Bag-of-Words (BoW) model
  • Understanding stop words
  • Understanding vectorization and transformers
  • Some examples
  • Conclusion
8

Implementing Speech Recognition with Python

  • Introduction
  • Basics of speech recognition
  • Building a speech recognizer
  • Conclusion
  • Questions
9

Implementing Artificial Neural Network (ANN) with Python

  • Introduction
  • Understanding of Artificial Neural Network (ANN)
  • Optimizers for training the neural network
  • Regularization
  • Installing useful Python package for ANN
  • Examples of building some neural networks
  • Conclusion
  • Questions
10

Implementing Reinforcement Learning with Python

  • Understanding reinforcement learning
  • Markov Decision Process (MDP)
  • Building blocks of reinforcement learning
  • Constructing an environment using Python
  • Constructing an agent using Python
  • Conclusion
  • Questions
11

Implementing Deep Learning and Convolutional Neural Network

  • Introduction
  • Understanding Deep Learning
  • Elucidation of Convolutional Neural Networks
  • The Architecture of Convolutional Neural Network
  • Localization and object recognition with deep learning
  • Image classification using CNN in Python
  • Conclusion
  • Questions

Learn AI with Python

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