Join Sign in

Kevin Quigley

Member since 2023

Badge for Generative AI Fundamentals Generative AI Fundamentals Earned يونيو 8, 2023 EDT
Badge for Create Image Captioning Models Create Image Captioning Models Earned يونيو 5, 2023 EDT
Badge for Transformer Models and BERT Model Transformer Models and BERT Model Earned يونيو 5, 2023 EDT
Badge for Attention Mechanism Attention Mechanism Earned يونيو 5, 2023 EDT
Badge for Encoder-Decoder Architecture Encoder-Decoder Architecture Earned يونيو 5, 2023 EDT
Badge for Introduction to Image Generation Introduction to Image Generation Earned يونيو 5, 2023 EDT
Badge for Introduction to Responsible AI Introduction to Responsible AI Earned يونيو 5, 2023 EDT
Badge for Introduction to Large Language Models Introduction to Large Language Models Earned يونيو 5, 2023 EDT
Badge for Introduction to Generative AI Introduction to Generative AI Earned يونيو 5, 2023 EDT

Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. By passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

Learn more

This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images

Learn more

This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.

Learn more

This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.

Learn more

This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.

Learn more

This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.

Learn more

This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 7 AI principles.

Learn more

This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.

Learn more

This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

Learn more