Fundamentals Of Generative AI
Fundamentals Of Generative AI
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Published 12/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 986.56 MB | Duration: 1h 19m
Master all Importance basics of Generative AI with examples and Learn more about generative
What you'll learn
Learn how to use Generative AI in Learning and Development the skills
Learn How to generate Automated Content with Generative AI
Master some vital Generative and ChatGPT for learning and development
Learn how to use ChatGPT in learning and development
Requirements
You must have a working computer
Description
Generative AI is a branch of artificial intelligence that focuses on creating models capable of generating new, human-like content such as text, images, music, or code. It is underpinned by deep learning and neural networks, which allow machines to learn patterns from vast datasets and produce novel outputs. Unlike traditional AI systems designed to perform specific tasks or make decisions based on predefined rules, generative AI models aim to simulate creativity by creating original and contextually relevant content.Generative AI has numerous applications, spanning multiple industries. In natural language processing, it powers chatbots, virtual assistants, and automated content creation tools. In visual domains, it is used for designing graphics, generating realistic images, and enhancing creative workflows. In healthcare, generative AI supports drug discovery, simulates medical scenarios, and aids in diagnostic imaging. It also plays a role in personalized education and entertainment, offering tailored solutions to users. For instance, a text-based model like GPT is trained on vast corpora of written material to learn grammar, syntax, and context. Through this training, the model identifies patterns and constructs probabilistic representations, allowing it to produce outputs that align with the training data's style and structure.Generative AI blends computational power and creativity, offering tools that augment human capabilities. As it evolves, its fundamental principles-data, algorithms, and training-will continue to drive its transformative impact, shaping the future of technology and society.
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Generative AI Basics
Lecture 2 What is Generative AI
Lecture 3 Generative AI NLP
Section 3: Data ingestion in Generative AI
Lecture 4 Data Ingestion and Preperation in Generative AI
Lecture 5 Generative AI Various Commands
Section 4: Interface in Generative AI
Lecture 6 Interface of Jupyter in Generative AI
Lecture 7 Version Control System in Generative AI
It is for those who want to learn with Generative AI and ChatGPT
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