Advanced Chatbots with Deep Learning and Python - Steps Involved

Advanced Chatbots with Deep Learning and Python - Steps Involved

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial covers the development of a deep learning-based chatbot. It begins with package installation, followed by defining chat models and selecting the appropriate one. The process of tokenization is explained, focusing on deep learning requirements. An encoder-decoder model is set up, and an RNN-based model is implemented. Finally, the chatbot is tested, trained, and validated to ensure its effectiveness in real-world scenarios.

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5 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the first step in developing a deep learning-based chatbot?

Testing the chatbot

Defining a chat model

Installing necessary packages

Tokenizing the corpus

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which process involves breaking down text into smaller units for deep learning?

Tokenization

Model validation

Package installation

Chat model definition

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What model setup is crucial for developing a chatbot in this tutorial?

Convolutional Neural Network

Support Vector Machine

Encoder-Decoder Model

Decision Tree

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which type of model is implemented towards the end of the chatbot development process?

RNN-based model

KNN-based model

SVM-based model

CNN-based model

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the final step in the chatbot development process discussed in the tutorial?

Tokenizing the corpus

Defining the chat model

Testing, training, and validating the chatbot

Installing packages

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