Machine learning allows software apps to improve their prediction accuracy without being expressly designed to do so by using historical data as input.

MLOps aims to provide continuous integration and continuous delivery throughout the development lifecycle of an application.

A few of the main fields of AI & ML usage include; analytics and forecasting, hyper-automation, security, IoT devices, augment intelligence, etc.

Top AI software; Google Cloud Vertex AI, Nvidia Deep Learning, H20.ai, IBM Watson, Azure Machine Learning, Zoho SalesIQ, Microsoft Cortana, Deep Vision.

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State machines model explicit states to control the transition from one value to another in response to inputs.

Serverless architectures are application designs that incorporate third-party “Backend as a Service” (BaaS) services and cloud machine resources as needed.

Java Virtual Machines (JVMs) are a popular choice for microservice environments. Knowing Ratpack & Spring Boot helps in building a high performance JVM.

AI is a branch of computer science that endeavors to replicate as much as possible or to simulate human understandings and intelligence in machines.

Learning and mastering the three pillars of Understanding, Managing, and Preventing is essential to effectively troubleshoot Kubernetes.

The components of AI are 1. Learning, 2. AI Reasoning, 3. Problem Solving, 4. Perception, 5. Processing Language

Collaboration between developers made easier with the Git software. Get the most from the Git tool by learning a few of its main commands with examples.