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Docker and Kubernetes course: Practical Guide (AWS platform). Course description: Part 1. Introduction to Kubernetes Part 3. Closing. Claster Cluster AWS Kubernetes. Part 4. Focus on the clusters Kubernetes, Mini-Heroch, Yaml, Pod, Kublet, server ports. Section 5: Road policy Kubernetes Section 6: Tags and selectors Section 7: Increase and rest Section 8: Deployment and Return … Read more

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Docker and Kubernetes course: Practical Guide (AWS platform). Course description: Part 1. Introduction to Kubernetes Part 3. Closing. Cluster setting AWS Kubernetes. Part 4. Focus on the clusters Kubernetes, Mini-Heroch, Yaml, Pod, Kublet, server ports. Section 5: Road policy Kubernetes Section 6: Tags and selectors Section 7: Increase and rest Section 8: Deployment and Return … Read more

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Docker and Kubernetes Course: A Practical Guide (AWS Platform). Course Description: Part 1: Introduction to Kubernetes Part 3: Setting up an AWS Kubernetes cluster environment Part 4: Kubernetes Concepts – Cluster Types, Minikube Server, Yaml, Pod, Kublet, Ports Section 5: Kubernetes Pod Reload Policy Section 6: Tags and Selectors Section 7: Scaling and Iteration Section … Read more

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Docker and Kubernetes Course: A Practical Guide (AWS Platform). Course Description: Part 1: Introduction to Kubernetes Part 3: Setting up an AWS Kubernetes cluster environment Part 4: Kubernetes Concepts – Cluster Types, Minikube Server, Yaml, Pod, Kublet, Ports Section 5: Kubernetes Pod Reload Policy Section 6: Tags and Selectors Section 7: Scaling and Iteration Section … Read more

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Docker and Kubernetes Course: A Practical Guide (AWS Platform). Course Description: Part 1: Introduction to Kubernetes Part 3: Setting up an AWS Kubernetes cluster environment Part 4: Kubernetes Concepts – Cluster Types, Minikube Server, Yaml, Pod, Kublet, Ports Section 5: Kubernetes Pod Reload Policy Section 6: Tags and Selectors Section 7: Scaling and Iteration Section … Read more

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Applied machine learning: algorithms course. Given the growing importance of machine learning in almost every field, professionals need a deeper understanding and practical approach to effectively implement machine learning algorithms. This course covers common machine learning algorithms. Course instructor Matt Harrison focuses on shallow learning algorithms and covers PCA, clustering, linear and logistic regression, decision … Read more