Advanced chatbots with deep learning & Python / Shahzaib Hamid, AI Sciences instructor.

Format:

Video

Contributor:

Hamid, Shahzaib, speaker, instructor.

Packt Publishing, publisher.

AI Sciences (Firm), presenter.

Series:

Academic Video Online

Language:

English

Subjects (All):

Chatbots.

Deep learning (Machine learning).

Machine learning.

Python (Computer program language).

Artificial intelligence.

Human-computer interaction.

Genre:

Instructional films.

Physical Description:

1 online resource (119 minutes)

Edition:

[First edition].

Other Title:

Advanced chatbots with deep learning and Python

Title on screen: Chatbots development with deep learning

Place of Publication:

Birmingham, England : PACKT Publishing, 2023.

Language Note:

In English.

System Details:

video file

Summary:

Have you ever wanted to build a simple, easy, and efficient chatbot for your business or needed an efficient instructor for your education? If yes, this is the ideal course that will benefit your interests. About This Video: Learn basic to advanced mechanisms of developing chatbots using deep learning with Python. Use Python to evaluate datasets based on conversational notes, online resources, and websites. Explore conventional/self-learning chatbots in action and chatbot development with deep learning. In Detail: AI-powered chatbots are also capable of automating various tasks, including sales and marketing, customer service, and administrative and operational tasks. In this course about developing advanced chatbots with deep learning, we will understand their applications and build from scratch using deep learning with Python. The course begins with a brief overview and the fundamentals of deep learning for chatbots. We will understand and compare conventional chatbots with deep learning-based chatbots. Then, we will explore self-learning chatbots, including generative chatbots and retrieval chatbots. You will learn more about deep learning-empowered chatbot features and compare and distinguish the abilities of conventional chatbots and self-learning chatbots in real action. We will focus on chatbot development with deep learning, tokenization, setting up an Encoder-Decoder, implementing RNN-based model development, and finally, training, testing, and validating the chatbot we developed. Upon completing this course successfully, you will relate concepts and understand theories of chatbots in various domains, understand and implement deep learning models for building real-world chatbots, and evaluate deep learning-based chatbot models. All resources are available at GitHub.

Participant:

Shahzaib Hamid, presenter.

Notes:

Title from resource description page (viewed October 10, 2023).

Title from resource description page (viewed December 04, 2023).

OCLC:

1373633740