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Develop a Chatbot Using Python, NLTK, and TensorFlow

PROJECT


Develop a Chatbot Using Python, NLTK, and TensorFlow

In this project, we’ll learn to develop a custom chatbot using Python APIs of the Natural Language Toolkit (NLTK) library and TensorFlow. The chatbot will be a simple one whose functions can be built on and further enhanced.

Develop a Chatbot Using Python, NLTK, and TensorFlow

You will learn to:

Read and save data, using Python

Perform tasks like tokenization and lemmatization, using NLTK

Build, compile, and train the deep neural network

Save, reload, and utilize the trained model

Skills

Natural Language Processing

Python

Prerequisites

Basic understanding of coding in Python

Basic understanding of LSTM in TensorFlow (Keras)

Familiarity with natural language processing tasks

Technologies

NLTK

Python

Pillow

TensorFlow

Project Description

Learn to develop a chatbot by using deep learning techniques. The chatbot will be trained with a dataset including categories (intents), patterns, and responses. We’ll use a specialized recurrent neural network (LSTM) to detect the category of the user’s message, and the chatbot will choose a random response from a list of potential replies.

Project Tasks

1

Preliminaries

Task 1: Import the Required Libraries

Task 2: Load the Data

2

Preprocess the Data

Task 3: Tokenization

Task 4: Lemmatization

Task 5: Create Data for Training

3

Model Design and Deployment

Task 6: Design the Model

Task 7: Train and Save the Model

Task 8: Print the training curves

Live Demo

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Relevant Courses

Use the following content to review prerequisites or explore specific concepts in detail.