The Life-Long Journey of Learning!

Today I had the opportunity to attend "Personal Branding Session led by the renowned speaker and thought leader, Pradeep Soundararajan." The session was both enlightening and empowering, providing valuable insights into building a strong personal brand. This mind map provides a comprehensive overview of the key takeaways of personal branding from the session. 😊

Key Points: Generative AI is a type of AI that can create new content, such as images, text, and audio. Generative Image Models use techniques like diffusion to create images from prompts or existing images. Generative Language Models learn patterns in language from training data and can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way.   1. speechify.com speechify.com Predictive Models take data and labels as input, learn the relationship between them, and output the label. Prompt Design is the process of creating a prompt that will generate the desired output from a language model. Examples of Generative AI Applications: Image Generation: Creating images from text descriptions. Image Captioning: Generating text descriptions of images. Text Generation: Writing different kinds of creative content, translating languages, and answering questions. Translation: Translating text from one ...

Generative Model : Focuses on understanding and creating visual representations of data. It learns about the features and can generate new data instances. Discriminative Model : Focuses on distinguishing between different classes based on their features. It classifies data by learning the differences between classes. This mind map helps in understanding the key differences between generative and discriminative models in deep learning.

“The only way to do great work is to love what you do.” — Steve Jobs What is AI? : Describes AI as a discipline of computer science focused on building machines that think and act like humans. Generative AI : Explains that it produces text, images, audio, and synthetic data using artificial neural networks. Machine Learning : Highlights that it is a subfield of AI where models are trained with input data to learn without explicit programming. Deep Learning : A type of machine learning that uses artificial neural networks to process data.