THINK 2021 Lab Session 2124: Build & Deploy AI/ML Models with Multiple Datasets with AutoAI
Join us for the event on IBM Code Engine, a new platform developed by IBM that enables you to quickly run your containerized apps and jobs. From web apps, to micro-services, to event driven functions, or batch jobs, Code Engine abstracts away the operational burden of building, deploying, and managing these workloads in Kubernetes. Ultimately, Code Engine enables developers to focus on what matters most to them: the source code. 🎓What You Will Learn In this online meetup, you will learn about some of the Code Engine functionality that is available in IBM Cloud. This workshop agenda is the following: - Introduction to Code Engine - Deploy Your First Application w Code Engine 👩‍💻Who Should Attend Back End Developers Cloud Developers Full Stack Developers Serverless Developers AI Developers 🎙Speakers Doug Davis, IBM STSM and Offering Manager for Knative Jenna Ritten, IBM Cloud Developer Advocate
Learn how to secure OpenShift applications with IBM Cloud App ID. Explore modern user and microservice security for Cloud Native applications run on Red Hat OpenShift. Upon completion of this workshop, you will be able to: - Secure a web app that provides the user interface through the web browser and leverages externalize Authentication services based on IBM Cloud App ID OpenID Connect (OIDC) services. Specifically, the web app leverages the OIDC Authorization Grant Type. - Build a Java microservice that implements the Backend-for-frontend (BFF) pattern. The BFF and OIDC integration are implemented by using the Spring Boot framework and Spring Security related frameworks. The BFF microservice is packaged as a container leveraging Eclipse JKube automatic source-to-image and deployed to Red Hat OpenShift on IBM Cloud. - The Java Resource microservices returns a simple message. The microservice is implemented by using the Spring Boot framework and Spring Security related frameworks. The resource microservice is packaged as a container leveraging Eclipse JKube automatic source-to-image and deployed to Red Hat OpenShift on IBM Cloud. - Enable microservice-to-microservice security between the BFF and Resource microservice leverages the OIDC JSON Web Tokens (JWT) and the Java Web KeySet (JWKS) Public Keys.
Learn how to use Juypter Notebooks in a secure cloud environment to analyze data. You will learn how to prepare and normalize the data for machine model building, perform sentiment analysis by using machine learning algorithms, and finally deploy the model so that it can be accessed outside of the notebook. Learning Outcomes : - Basics of Jupyter Notebooks on Watson Studio - Learn how to perform sentiment analysis and deploy data in a Jupyter Notebook ** Get a head start by signing up for a free IBM Cloud account via → http://ibm.biz/debater_cloud **
Deploy a Blockchain application for payload management in satellite manufacturing using Hyperledger Fabric 1.4 utilizing ABAC feature. This workshop is for Blockchain developers interested in developing a web application to connect to a Hyperledger Fabric 1.4 network. The use case discussed is Payload management in satellite manufacturing. What is covered? - Bring up a simple Hyperledger Fabric network using VSCode Blockchain extension - Set up a Smart Contract - Run a Web application which connects to the network - Demonstrate use of Attribute Based Access Control (ABAC) feature of Hyperledger Fabric. Prerequisites: Fundamental understanding of Blockchain basics Working knowledge of Hyperledger Fabric
🔍 How do you remove bias from the machine learning models and ensure that the predictions are fair? What are the three stages in which the bias mitigation solution can be applied? In this workshop we will answer these questions to help you make informed decision by consuming the results of predictive models. 🔍 Fairness in data and machine learning algorithms is critical to building safe and responsible AI systems. While accuracy is one metric for evaluating the accuracy of a machine learning model, fairness gives you a way to understand the practical implications of deploying the model in a real-world situation. 🔑 In this workshop, you will use a diabetes data set to predict whether a person is prone to have diabetes. You’ll use IBM Watson Studio, IBM Cloud Object Storage, and the AI Fairness 360 Toolkit to create the data, apply the bias mitigation algorithm, and then analyze the results. After completing this workshop, you will understand how to: - Create a project using Watson Studio - Use the AI Fairness 360 Toolkit