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Machine Learning Solutions

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

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788390040
Length 566 pages
Edition 1st Edition
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Table of Contents (19) Chapters Close

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

Problems with the existing approach


In this section, we will discuss the problems with the basic version of our chatbot. As we already know, for unseen queries this approach doesn't work, which means that the basic approach is not able to generalize the user's questions properly.

I have listed down some of the problems here:

  • Time consuming because we need to hardcode each and every scenario, which is not feasible at all

  • It cannot work for unseen use cases

  • The user should process the rigid flow of conversation

  • It cannot understand the long context

Most of these problems can be solved using the generative-based approach. Let's look at the key concepts that will help us improvise this approach.

Understanding key concepts for optimizing the approach

In this section, we will be discussing the key concepts that can help us improvise the chatbot basic version. The problems that we have listed down previously can be solved by using Deep Learning (DL) techniques, which can help us build a more generalized...

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