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Machine Learning Solutions

You're reading from Machine Learning Solutions Expert techniques to tackle complex machine learning problems using Python

Product type Paperback

Published in Apr 2018

Publisher Packt

ISBN-13 9781788390040

Length 566 pages

Edition 1st Edition

Languages

Python

Tools

OpenCV

Concepts

Machine Learning

Author (1):

Jalaj Thanaki

View More author details

Table of Contents (19) Chapters

Machine Learning Solutions

Foreword

Contributors

Preface

1. Credit Risk Modeling

2. Stock Market Price Prediction FREE CHAPTER

3. Customer Analytics

4. Recommendation Systems for E-Commerce

5. Sentiment Analysis

6. Job Recommendation Engine

7. Text Summarization

8. Developing Chatbots

9. Building a Real-Time Object Recognition App

10. Face Recognition and Face Emotion Recognition

11. Building Gaming Bot

List of Cheat Sheets

Strategy for Wining Hackathons

Index

Understanding datasets

In order to develop a chatbot, we are using two datasets. These datasets are as follows:

Cornell Movie-Dialogs dataset
bAbI dataset

Cornell Movie-Dialogs dataset

This dataset has been widely used for developing chatbots. You can download the Cornell Movie-Dialogs corpus from this link: https://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html. This corpus contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts.

This corpus has 220,579 conversational exchanges between 10,292 pairs of movie characters. It involves 9,035 characters from 617 movies. In total, it has 304,713 utterances. This dataset also contains movie metadata. There are the following types of metadata:

Movie-related metadata includes the following details:
- Genre of the movie
- Release year
- IMDb rating
Character-related metadata includes the following details:
- Gender of 3,774 characters
- Total number of characters in movies

When you download this dataset, you...

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Authors (1)

Jalaj Thanaki

Jalaj Thanaki

Jalaj Thanaki is an experienced data scientist with a demonstrated history of working in the information technology, publishing, and finance industries. She is author of the book Python Natural Language Processing, Packt publishing. Her research interest lies in Natural Language Processing, Machine Learning, Deep Learning, and Big Data Analytics. Besides being a data scientist, Jalaj is also a social activist, traveler, and nature-lover.

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