Using AI to Transform Search
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Using AI to Transform Search

Make your searches more responsive and smarter by applying Artificial Intelligence to it
0.0 (0 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
1 student enrolled
Created by Packt Publishing
Last updated 8/2017
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Current price: $10 Original price: $125 Discount: 92% off
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  • 2 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Where searches can be used
  • Understand the algorithms that can be used to make decisions more intelligent
  • Formulate a problem, that is, specify its initial state, goal state, and actions
  • Translate the concepts of the selected search algorithm into code
  • Compare how basic search algorithms will perform for the application
View Curriculum
  • A basic knowledge and understanding of Python are assumed.

With the emergence of big data and modern technologies, AI has acquired a lot of relevance in many domains. The increase in demand for automation has generated many applications for AI in fields such as robotics, predictive analytics, finance, and more.

In this course, you will understand what artificial intelligence is. It explains in detail basic search methods: DFS (Depth First Search), BFS (Breadth First Search), and A* search, which can be used to make intelligent decisions when the initial state, end state, and possible actions are known. Random solutions or greedy solutions can be found for such problems. But these are not optimal in either space or time and efficient approaches in time and space will be explored. We will also understand how to formulate a problem, which involves looking at it and identifying its initial state, goal state, and the actions that are possible in each state. We also need to understand the data structures involved while implementing these search algorithms as they form the basis of search exploration. Finally, we will look into what a heuristic is as this decides the quality of one sub-solution over another and helps you decide which step to take.

About The Author :

Devangini Patel is a Ph.D. student at the National University of Singapore, Singapore. Her research interests include Deep Learning, Computer Vision, Machine Learning and Artificial Intelligence. She has completed masters in Artificial Intelligence from University of Southampton, UK. She has over 5 years of experience in the field of AI and has worked on various industrial and research projects in AI including facial expression analysis, robotics, virtual try-on, object recognition and detection and advertisement ranking.

Who is the target audience?
  • This video is for developers who are keen to get started with Artificial Intelligence and develop practical AI-based applications. Those developers who want to upgrade their normal applications to smart and intelligent versions will find this tutorial useful.
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Curriculum For This Course
21 Lectures
Shortest Time Search (Depth First Search)
9 Lectures 46:41

This video provides an overview of the entire content.

Preview 04:26

Set up the environment, download and install the required libraries required for this title.
Installation and Setup

Understand the application that we will develop in this section by answering the questions.
Introduction to File Search Application

Understand and implement the concept of state and the three main ingredients of search problems by answering the questions.
Search Problem Formulation

Build a sample search tree by answering the questions.

Building Search Tree with Nodes

Understand stack data structure by answering the questions.
Stack Data Structure

Understand the practical working of DFS algorithm by answering the questions.
DFS Algorithm

Understand recursive DFS by answering the questions.
Recursive DFS

Explains an application that you can develop yourself.
Do It Yourself
Shortest Path Search (Breadth First Search)
6 Lectures 25:01
Understand the application that we will be developing by answering the questions
Preview 06:26

Understand graph structure for this application by answering the questions

Graph Data Structure

Understand the basics of queue data structure by answering the questions
Queue Data Structure

Understand the flow of BFS.
BFS Algorithm

Compare both the algorithms.

DFS Versus BFS

Explain an application that you can develop yourself.

Do It Yourself
Heuristic Search
6 Lectures 45:25
Understand the application which we will be developing.
Preview 03:37

Understand the basics of priority queue data structure.
Priority Queue Data Structure

Understand how to visualize search tree.
Visualizing Search Tree

Understand the flow of Greedy Best First Search.
Greedy Best First Search Algorithm

Understand the flow of A* Search.
A* Search

Understand why we need heuristic.
What Is a Good Heuristic?
About the Instructor
Packt Publishing
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