Chatbots with Keras & NLP: Build & Evaluate
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Chatbots with Keras & NLP: Build & Evaluate
This course is part of Keras Deep Learning Projects with TensorFlow Specialization
Instructor: EDUCBA
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What you'll learn
Apply preprocessing and vectorization in NLP.
Build ML and neural chatbot models with Keras.
Evaluate and optimize conversational AI systems.
Skills you'll gain
Tools you'll learn
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12 assignments
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There are 3 modules in this course
Learners will be able to analyze text data, implement preprocessing techniques, apply vectorization methods, design machine learning and neural models, and evaluate advanced chatbot systems. This hands-on course guides learners step by step through the process of building chatbots with Keras and TensorFlow, ensuring both foundational and advanced skills are developed.
The course begins with essential NLP preprocessing techniques, including Bag of Words, TF-IDF, stop word removal, stemming, and lemmatization. Learners then progress to applying classical ML models, TF-IDF, and Word2Vec embeddings before mastering neural networks and generative chatbot architectures. In the final module, learners explore attention mechanisms, advanced architectures, and evaluation strategies to create context-aware, high-performing conversational AI. By completing this course, learners gain practical coding experience, industry-ready workflows, and the ability to confidently design and deploy chatbots for real-world applications. Unlike purely theoretical courses, this program emphasizes hands-on implementation, progressive complexity, and evaluation-driven learningβmaking it uniquely suited for those who want to design, implement, and assess intelligent chatbots with cutting-edge NLP techniques.
This module introduces learners to the essential foundations of Natural Language Processing (NLP) for chatbot development. It covers preprocessing techniques, feature extraction methods, and the basics of text normalization that ensure clean and structured input for building intelligent chatbot systems.
What's included
10 videos4 assignments
10 videosβ’Total 85 minutes
- Introduction to Projectβ’6 minutes
- Bow Modelβ’8 minutes
- Count Vectorizerβ’11 minutes
- Text Dataβ’8 minutes
- Text Data Continueβ’10 minutes
- Limit Number of Featuresβ’8 minutes
- Stop Wordsβ’8 minutes
- Stemmingβ’11 minutes
- Stemming Continueβ’10 minutes
- Lemmatizationβ’7 minutes
4 assignmentsβ’Total 60 minutes
- Foundations of Text and Preprocessing β Graded Quizβ’30 minutes
- Getting Started With Text Projectsβ’10 minutes
- Preparing and Cleaning Text Dataβ’10 minutes
- Mastering Text Normalizationβ’10 minutes
This module transitions from classical machine learning techniques to neural approaches for chatbot building. Learners will explore vectorization strategies like TF-IDF and Word2Vec, implement models using Keras, and gain practical experience with hands-on coding and neural network fundamentals.
What's included
9 videos4 assignments
9 videosβ’Total 71 minutes
- ML Model on Text Dataβ’8 minutes
- TF-TF-IDF Vectorizerβ’6 minutes
- Spacy Word2Vecβ’9 minutes
- Requirementsβ’7 minutes
- Hindson Implementationβ’7 minutes
- Hindson Implementation Continueβ’9 minutes
- Neural Networksβ’9 minutes
- Generative Chatbots Part 1β’10 minutes
- Generative Chatbots Part 2β’7 minutes
4 assignmentsβ’Total 60 minutes
- Classical and Neural Approaches β Graded Quizβ’30 minutes
- From Vectors to Modelsβ’10 minutes
- Setting Up and Implementingβ’10 minutes
- Neural Foundations for Chatbotsβ’10 minutes
This module delves into advanced chatbot architectures, including generative models with attention mechanisms and performance evaluation strategies. Learners will master cutting-edge NLP methods to design, implement, and evaluate context-aware and high-performing chatbot systems.
What's included
9 videos4 assignments
9 videosβ’Total 73 minutes
- Generative Chatbots Part 3β’12 minutes
- Generative Chatbots Part 4β’12 minutes
- Generative Chatbots Part 5β’6 minutes
- Attentive Chatbots Part 1β’11 minutes
- Attentive Chatbots Part 2β’6 minutes
- Attentive Chatbots Part 3β’5 minutes
- Advanced Chatbotβ’11 minutes
- Advanced Chatbot - Evaluationβ’3 minutes
- Conclusionβ’6 minutes
4 assignmentsβ’Total 60 minutes
- Building Advanced Chatbots β Graded Quizβ’30 minutes
- Generative Chatbots Deep Diveβ’10 minutes
- Attention and Contextβ’10 minutes
- Beyond Basics β Advanced Chatbotsβ’10 minutes
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Reviewed on May 5, 2026
The course provides a deep understanding of Keras for NLP. The evaluation frameworks are a unique addition that adds immense professional value to the curriculum.
Reviewed on Jun 2, 2026
The instructor makes advanced deep learning concepts feel effortless. Complex NLP logic is broken down into simple, logical pieces.
Reviewed on May 29, 2026
I appreciate how the course treats NLP as a rigorous science rather than just a coding trick. The clarity on hyperparameter tuning was a major highlight for me.
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