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Generative AI Explained: With Practical Hands-on (GAN + VAE + Diffusion Models)

By - Analytics Vidhya

šŸ“š Course Information

Channel

Analytics Vidhya

Published On

6/23/2023

šŸ“ Description

šŸ‘‰ Free Resources Download link: https://drive.google.com/drive/folders/1KH986zELtqJ24bsKmBEp_k49W4bc_DeX?usp=sharing Generative AI has taken up the world by storm. One of the most widely used examples of Generative AI is the renowned ChatGPT. This video covers the incredible capabilities and practical applications of Generative AI models. Generative AI, a cutting-edge technology, holds immense potential in today's technological landscape. It enables machines to generate new content based on existing data, revolutionizing fields such as computer vision, image generation, and content creation. We discuss the underlying techniques and algorithms that power these models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs) and other state-of-the-art approaches. Moreover, we showcase real-world examples and practical demonstrations of how pre-trained GAN models can generate new images and content. šŸ‘‰ Who is this DataHour for? ---- Students & Freshers who want to build a career in the Data-tech domain ---- Working professionals who want to transition to the Data-tech domain ---- Data science professionals who want to accelerate their career growth ---- Prerequisites: Knowledge of Python packages, Linear Algebra, Probability, and Machine Learning šŸ‘‰ About the Speaker: Abhishek, a highly skilled and experienced professional, currently serves as a Data Scientist at Reliance Jio. With over four years of exceptional performance in the field of data science, he is considered an expert in computer vision. Abhishek's extensive academic background is equally impressive, having earned a master's degree in computer science from the prestigious Indian Institute of Technology (IIT), Bombay. His academic excellence and industry experience have made him a valuable asset to his company and an inspiring role model for aspiring data scientists.

šŸŽÆ What You'll Learn

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Complete understanding of the topic

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Hands-on practical knowledge

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Real-world examples and use cases

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Industry best practices

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šŸ“‹ Prerequisites

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    Basic understanding of programming concepts

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    Eagerness to learn and practice

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Course Content

Introduction Section (0 sec - 14 min)
1
14 min

Introduction Section (0 sec - 14 min)

5 Questions Ready
Main Content Section 1 (14 min - 28 min)
2
14 min

Main Content Section 1 (14 min - 28 min)

5 Questions Locked
Main Content Section 2 (28 min - 43 min)
3
14 min

Main Content Section 2 (28 min - 43 min)

5 Questions Locked
Final Section (43 min - 57 min)
4
14 min

Final Section (43 min - 57 min)

5 Questions Locked
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