Samprad Raja Uprety
Date d'abonnement : 2024
Ligue d'Argent
19260 points
Introduction to Image Generation
Earned jan. 2, 2025 EST
Machine Learning Operations (MLOps) for Generative AI
Earned jan. 2, 2025 EST
[Depricated] Build, Train and Deploy ML Models with Keras on Google Cloud
Earned jan. 2, 2025 EST
[DEPRECATED] Feature Engineering
Earned jan. 2, 2025 EST
Engineer Data for Predictive Modeling with BigQuery ML
Earned jan. 2, 2025 EST
Create ML Models with BigQuery ML
Earned jan. 1, 2025 EST
Working with Notebooks in Vertex AI
Earned jan. 1, 2025 EST
Prepare Data for ML APIs on Google Cloud
Earned jan. 1, 2025 EST
Introduction to AI and Machine Learning on Google Cloud
Earned jan. 1, 2025 EST
Quiz: GDC Air-Gapped Practitioner Fundamentals
Earned jan. 1, 2025 EST
AI Services and GDC Deployments and Operations
Earned déc. 31, 2024 EST
Compute, Network, and Storage Services Configuration in GDC
Earned déc. 31, 2024 EST
Build a Certification Study Guide: PMLE
Earned déc. 31, 2024 EST
GDC Platform Introduction
Earned déc. 31, 2024 EST
Introduction to Generative AI
Earned déc. 31, 2024 EST
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 Gemini Enterprise Agent Platform.
En savoir plus
This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
En savoir plus
This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
En savoir plus
This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
En savoir plus
Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.
En savoir plus
Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.
En savoir plus
This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
En savoir plus
Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
En savoir plus
This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
En savoir plus
This quiz tests your GDC Air-Gapped Practitioner Fundamentals knowledge.
En savoir plus
The course explores advanced services such as machine learning, and operational topics such as application deployment, monitoring, and troubleshooting.
In addition, we’ll introduce GDC software upgrades, logging, billing, and cost monitoring.
En savoir plus
The course examines service resources or workload components that exist in projects. You’ll learn about Kubernetes in GDC, Artifact Registry, GDC Object Storage, Database Service, Networking, and Key Management and Security.
En savoir plus
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.
En savoir plus
This course provides an introduction to the GDC platform—which enables you to host, control, and manage infrastructure and services directly on your premises.
GDC air-gapped is one component of Google Distributed Cloud offering which aligns to Google’s digital sovereignty vision. It supports public-sector customers and commercial entities that have strict data residency, security or privacy requirements.
En savoir plus
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.
En savoir plus
