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