Basics of Chatbots with Machine Learning & Python

Resumen

This course offers a thorough exploration of chatbots and their development using machine learning and Python. You’ll start with an introduction to chatbots, including their history and various applications across industries.

The course then delves into the distinctions between chatbots, virtual assistants, and personal assistants, providing a comprehensive overview of their respective benefits and challenges.

As you progress, you’ll focus on machine learning-based chatbots, exploring their architecture, features, and the revolutionary impact of ML on customer service, healthcare, and more. You’ll gain practical experience by working with the Natural Language Toolkit (NLTK) to develop rule-based chatbots, covering essential topics such as data input, word tokenization, lemmatization, and response generation.

The course also covers advanced concepts like Wikipedia search integration and local search mechanisms, enabling you to build more robust and interactive chatbots.

Finally, you will apply everything you’ve learned in a project where you develop a conversational chatbot from scratch. You’ll handle data collection, preprocessing, and response generation using sophisticated techniques like TF-IDF and cosine similarity.

By the end, you’ll have a fully functional chatbot and a deep understanding of the principles and practices of chatbot development, positioning you to leverage AI in real-world applications.

This course is ideal for software developers, data scientists, and AI enthusiasts who want to build chatbots using machine learning and Python. A basic understanding of Python programming is required, and familiarity with machine learning concepts will be beneficial but not mandatory.

University:

Coursera

Categories:

Python Courses, Machine Learning Courses, Chatbot Courses, Natural Language Toolkit (NLTK) Courses, Conversational AI Courses, TF-IDF Courses

Materias