Another week, and yet another Arcade Mystery! You'll want to warm up your mental muscles before you start your March Adventure in the Cloud by filling in some blanks!
Filling in the blanks can enhance learning and recall while providing clarity, facilitate effective problem-solving through critical thinking, and contribute to personal development by fostering adaptability and growth. That's what our next Arcade Mystery is all about!
All you need to do is fill in the blanks with the correct answers to the questions below and three lucky winners will receive 25 GCSB credits, worth $25!
So let’s get started!
1. _____________ works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2.________ is a managed service for storing unstructured data.
3._________________ let you operate apps on multiple identical VMs.
4 ._________ is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a ________ to deploy and launch a Docker container.
All the best! May the brightest minds in the Community win!
See you in the Cloud!
Natural Language Processing (NLP) works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
Amazon S3 is a managed service for storing unstructured data.
Container Orchestration tools let you operate apps on multiple identical VMs.
Amazon Redshift is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
You can configure a Container Orchestration System to deploy and launch a Docker container.
1. Generative AI
2. Google Cloud Storage (GCS)
3. Managed Instance Group (MIG)
4. BigQuery
5.u Virtual machine (VM) instance or an instance template
1.Generative AI
2.Cloud Storage
3.kubernetes
4.Bigquery
5.Virtual Machines
1. Generative AI
2. Google Cloud Storage (GCS)
3. Managed Instance Group (MIG)
4. BigQuery
5. Virtual machine (VM) instance or an instance template
1.Generative AI
2.Cloud Storage
3.Hypervisor
4.Bigquery
5.Virtual Machines
#googlecloudcommunity #arcade
1. Generative AI
2. Google cloud storage
3. Load balancers in Google Cloud Platform (GCP)
4. Bigquery
5. virtual machine (VM) instance
1. Generative AI
2. Cloud Storage
3. Managed Instance Groups (MIGs)
4. Bigquery
5. Virtual Machine Instance (Compute engine)
1.Generative AI
2.Google Cloud Storage
3.Hypervisor
4.Bigquery
5.Virtual Machines
Hi @Yugali , Please find the answers below
1.Generative AI
2.Cloud Storage
3.Hypervisor
4.Bigquery
5.Virtual Machines
Hi @Yugali , hear is the answers
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Cloud Storage is a managed service for storing unstructured data.
3. Kubernetes let you operate apps on multiple identical VMs.
4. BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can be configured a CI/CD pipeline to deploy and launch a Docker container.
Hi @Yugali here are the answers
1.GENERATIVE AI
2.Google cloud Storage(GCS)
3.Managed Instance Group(MIGs)
4.BigQuery(BQ)
5.Cloud Run
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Google Cloud Storage is a managed service for storing unstructured data.
3. Compute Engine: Managed instance groups (MIGs) let you operate apps on multiple identical VMs.
4. BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data
5. You can configure a virtual machine (VM) instance or an instance template to deploy and launch a Docker container.
Natural Language Processing (NLP) works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
Amazon S3 is a managed service for storing unstructured data.
Container Orchestration tools let you operate apps on multiple identical VMs.
Amazon Redshift is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
You can configure a Container Orchestration System to deploy and launch a Docker container.
1. Natural Language Processing (NLP) works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Amazon S3 is a managed service for storing unstructured data.
3. Container Orchestration tools let you operate apps on multiple identical VMs.
4. Amazon Redshift is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a Container Orchestration System to deploy and launch a Docker container.
1. Generative AI
2. Cloud Storage
3. Managed Instance Groups (MIGs)
4. Bigquery
5. Virtual Machine Instance (Compute engine
1. AutoML: works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Cloud Storage: is a managed service for storing unstructured data.
3. Managed Instance Groups: let you operate apps on multiple identical VMs.
4. BigQuery: is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a Compute Engine instance to deploy and launch a Docker container.
1. Generative AI
2. Cloud Storage
3. Managed Instance Groups (MIGs)
4. Bigquery
5. Virtual Machine Instance (Compute engine)
1] Generative AI
2] Cloud Storage
3] kubernetes
4] Big Query
5] Virtual Machines
1. Generative AI
2. Google cloud storage
3. Load balancers in Google Cloud Platform (GCP)
4. Bigquery
5. virtual machine (VM) instance
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Cloud Firestore is a managed service for storing unstructured data.
3. Managed Instance Group let you operate apps on multiple identical VMs.
4 . Big Query is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a Google Kubernetes Engine or Cloud Run to deploy and launch a Docker container.
1 . Generative AI 2. Cloud Storage 3. Hypervisor 4. Bigquery 5. VM Instance or an Instance Template
Participant
1. Natural Language Processing (NLP) works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Amazon S3 (Simple Storage Service) is a managed service for storing unstructured data.
3. Google Kubernetes Engine (GKE) let you operate apps on multiple identical VMs.
4. Amazon Redshift is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure an Amazon Elastic Compute Cloud (EC2) instance to deploy and launch a Docker container.
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Google Cloud Storage is a managed service for storing unstructured data.
3. Compute Engine: Managed instance groups (MIGs) let you operate apps on multiple identical VMs.
4. BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a virtual machine (VM) instance or an instance template to deploy and launch a Docker container.
Hello @Yugali , please find the answers below :
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Cloud Storage is a managed service for storing unstructured data.
3. Managed instance groups (MIGs) let you operate apps on multiple identical VMs.
4 . BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a virtual machine (VM) instance to deploy and launch a Docker container.
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2.GCP Cloud Storage is a managed service for storing unstructured data.
3. Managed instance groups (MIGs) let you operate apps on multiple identical VMs.
4 .BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a virtual machine (VM) instance or an instance template to deploy and launch a Docker container.
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Cloud Firestore is a managed service for storing unstructured data.
3. Managed Instance Group let you operate apps on multiple identical VMs.
4 . Big Query is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a Google Kubernetes Engine or Cloud Run to deploy and launch a Docker container.
Vertex AI or Generative AI (GenAI) works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
Google Cloud Storage is a managed service for storing unstructured data.
Managed Instance Groups (MIGs) let you operate apps on multiple identical VMs.
BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
You can configure a virtual machine (VM) instance to deploy and launch a Docker container.
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Cloud Storage is a managed service for storing unstructured data.
3.Compute Engine: Managed instance groups let you operate apps on multiple identical VMs.
4 .BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a virtual machine (VM) instance or an instance template to deploy and launch a Docker container.
1- answer-Natural Language Processing (NLP)
2-answer-Amazon S3 (Simple Storage Service)
3-answer- load balancer
4-answer-Amazon Redshift
5-answer-Kubernetes
1. Generative AI
2. Google Cloud Storage
3. Managed Instance Groups (MIGs)
4. BigQuery
5. Virtual Machine Instance
1. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2. Cloud Storage is a managed service for storing unstructured data.
3. Container Orchestration tools let you operate apps on multiple identical VMs.
4 . Bigquery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a virtual machine (VM) instance or an instance template to deploy and launch a Docker container.
1. _Generative AI_ works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2._Google Cloud Storage_ is a managed service for storing unstructured data.
3._Managed Instance Group_ let you operate apps on multiple identical VMs.
4 ._BigQuery_ is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5. You can configure a _virtual machine (VM) instance or an instance template_ to deploy and launch a Docker container.
1. Generative AI
2. Cloud Storage
3. Managed Instance Groups (MIGs)
4. Bigquery
5. Virtual Machine Instance (Compute engine)
1) Natural Language Processing (NLP) works by using an ML model to learn the patterns and relationships in a dataset of human-created content.
2) Google Cloud Storage is a managed service for storing unstructured data.
3) Google Kubernetes Engine (GKE) lets you operate apps on multiple identical VMs.
4) Google BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.
5) You can configure a Google Compute Engine instance to deploy and launch a Docker container.
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