Curated Video
Data Science Model Deployments and Cloud Computing on GCP - HTTP Methods
This video explains HTTP methods, where predefined verbs are used to describe the interaction that the client wishes to engage in with the server, often called a request. The most common HTTP methods are GET, POST, PUT, and DELETE. This...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Special Mention - AngularJS Versus Angular
This video explains the difference between AngularJS and Angular, which is written using JavaScript and TypeScript simultaneously. This clip is from the chapter "Libraries and Front-End Frameworks" of the series "Web Development Concepts...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Front-End Frameworks with Angular
Developed by Google, Angular is a front-end framework that utilizes the TypeScript Superset. It is an opinionated framework that has many architectural decisions already made for developers. This clip is from the chapter "Libraries and...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Front-End Frameworks
This video explains the various front-end frameworks. This clip is from the chapter "Libraries and Front-End Frameworks" of the series "Web Development Concepts for Everyone".This video explains libraries and front-end frameworks.
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Library Example with Chart.js
This video explains Chart.js, a popular charting library for JavaScript. It makes what would be a difficult combination of styling, layout, and data positioning into an easy to manage ordeal, saving developers loads of time in creating...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Runtime Environments
This video explains the runtime environment where an application, which is the result of writing code, is executed. This clip is from the chapter "Programming Languages" of the series "Web Development Concepts for Everyone".In this...
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Data Science Model Deployments and Cloud Computing on GCP - GitHub
This video explains GitHub, which is a popular Git cloud platform used by individual developers and companies. This clip is from the chapter "Version Control" of the series "Web Development Concepts for Everyone".This video explains...
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Data Science Model Deployments and Cloud Computing on GCP - Merging
This video explains merging, which happens when a branch of new functionality is completed and ready to be brought back into the main development branch and ready to use. This clip is from the chapter "Version Control" of the series "Web...
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Data Science Model Deployments and Cloud Computing on GCP - Branching
This video explains branching, which is a copy of the code base of a commit. The branch is a copy of the last commit and all the commits that came before it. This clip is from the chapter "Version Control" of the series "Web Development...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Introduction to Git
This video explains Git, which is the most popular version control technology. Git pairs with popular platforms such as GitHub, Bitbucket, and GitLab. It allows for version branching. This clip is from the chapter "Version Control" of...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Introduction to Version Control
This video introduces you to version control, which is a technology that supports versioning of in-progress software. It is more advanced than just saving files. Version control gives developers flexibility to safely experiment and...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Server
This video explains the server that handles data exchanges between clients and databases. Users have the client on their device, so there are many clients. Those clients talk to the same server per application. This clip is from the...
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Data Science Model Deployments and Cloud Computing on GCP - Client
This video explains the client, which is a login that makes a webpage smart. It handles user interactions and flow of data between the user and server. The client is what turns a webpage into a web application. This clip is from the...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Frontend
This video explains the frontend, which is everything we can see on the webpage, which is a combination of layout and the style of all the elements on the screen. The This clip is from the chapter "The Basics of Full-Stack Web...
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Data Science Model Deployments and Cloud Computing on GCP - Lab - Deploy Training Code to App Engine
This is a lab video on deploying training code to App Engine. This clip is from the chapter "Data Science Models with Google App Engine" of the series "Data Science Model Deployments and Cloud Computing on GCP".This section focuses on...
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Data Science Model Deployments and Cloud Computing on GCP - Lab - Deploy Python Application to Cloud Run
In this video, we walk you through the process of deploying a Python application to Cloud Run, Google's fully managed serverless compute platform. This clip is from the chapter "Cloud Run - Serverless and Containerized Applications" of...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Lab - Set Up Alerting for Cloud-Run Applications
In this lab video, you will be setting up an alerting system for cloud-run applications. This clip is from the chapter "Cloud Scheduler and Application Monitoring" of the series "Data Science Model Deployments and Cloud Computing on...
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Data Science Model Deployments and Cloud Computing on GCP - Lab - Cloud Scheduler in Action
In the lab video, you will learn about Cloud Scheduler, which is a fully managed enterprise job scheduler for calling services within and outside of Google Cloud. By the end of this lab, you will have a solid understanding of how to use...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Lab - Pipeline Execution in Kubeflow
In this lab video, you will learn to use the Kubeflow for pipeline execution. This clip is from the chapter "Vertex AI - Machine Learning Framework" of the series "Data Science Model Deployments and Cloud Computing on GCP".In this...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Lab - Code Walkthrough Using Kubeflow and Python
This is a lab video that will help you with a code walkthrough using Kubeflow and Python. This clip is from the chapter "Vertex AI - Machine Learning Framework" of the series "Data Science Model Deployments and Cloud Computing on GCP".In...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Lab - Model Serving Using Endpoint with Python SDK
In this lab video, you will learn how to serve a machine learning model using the Vertex AI Prediction service. You will use a pre-trained model and create an endpoint to make predictions on new data. This clip is from the chapter...
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Data Science Model Deployments and Cloud Computing on GCP - Lab - Model Training Flow Using Python SDK
In this lab video, you will learn how to create a model training flow using the Vertex AI Python SDK. This clip is from the chapter "Vertex AI - Machine Learning Framework" of the series "Data Science Model Deployments and Cloud...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Lab - Custom Model Training Using SDK and Model Registries
In this lab video, you will learn how to use the Vertex AI SDK and model registries to train and deploy custom machine learning models. This clip is from the chapter "Vertex AI - Machine Learning Framework" of the series "Data Science...
Curated Video
Data Science Model Deployments and Cloud Computing on GCP - Persistent History Cluster
In this video, you will learn about persistent history cluster in Google Cloud Dataproc, which allows you to store cluster metadata such as logs and job history on a persistent disk. This clip is from the chapter "Dataproc Serverless...