Book Image

Artificial Intelligence with Python - Sequence Learning [Video]

By : Prateek Joshi
Book Image

Artificial Intelligence with Python - Sequence Learning [Video]

By: Prateek Joshi

Overview of this book

<p>Enter and explore the fascinating world of intelligent apps with Artificial Intelligence with Python. Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps that intelligently interact with the world around you, automatic speech recognition systems, and more.</p> <h2>Style and Approach</h2> <p>This course takes a concept-based, explanation-focused approach. Each concept is explained and then the exercise or example is implemented.</p>

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Artificial Intelligence with Python - Sequence Learning [Video]
Prateek Joshi
Dec, 2017 | 1 hour 14 minutes
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Table of Contents (3 chapters)
Free Chapter
1
Natural Language Processing
The Course Overview
Introduction and Installation of Packages
Tokenizing Text Data
Converting Words to Their Base Forms
Dividing Text Data into Chunks
Extracting the Frequency of Terms Using a Bag of Words Model
Building a Category Predictor
Constructing a Gender Identifier
Building a Sentiment Analyzer
Topic Modeling Using Latent Dirichlet Allocation
2
Probabilistic Reasoning for Sequential Data
Understanding Sequential Data
Handling Time-Series Data with Pandas
Slicing Time-Series Data
Operating on Time-Series Data
Extracting Statistics from Time-Series Data
Generating Data Using Hidden Markov Models
Identifying Alphabet Sequences with Conditional Random Fields
Stock Market Analysis
3
Building a Speech Recognizer
Working with Speech Signals
Visualizing Audio Signals
Transforming Audio Signals to the Frequency Domain
Generating Audio Signals
Synthesizing Tones to Generate Music
Extracting Speech Features
Recognizing Spoken Words
Chapter 1
Natural Language Processing
Content Locked
Section 10
Topic Modeling Using Latent Dirichlet Allocation
We need to separate topics in text. Topic modeling helps with segment various texts into different topics. Let’s see how to do that in this video. - Process input text and stem it and remove stop words - Create a document-term matrix from sentence tokens - Generate the LatentDirichlet model and print the top words for each topic
Previous Section
End of Chapter 1
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