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Remote Working In a Post-Covid World
Whether you are in Real Estate, Engineering, Transport, Financial Services & Insurance, or Education Industry, how you work has been vastly affected by Covid-19 Pandemic., Globally, many businesses have suffered the shock of the turbulent times brought by the pandemic & have been forced to find inventive solutions to manage human capital. While it may be uncertain how a post-pandemic society will function, we all know that working from home has change how companies think about rigid work schedules.
Auto ML and Low Code ML
The field of machine learning has undergone significant growth and evolution in recent years, and this trend is likely to continue into the future. Two of the most notable trends in machine learning are the rise of auto ML and low-code machine learning. Auto ML, or automated machine learning, refers to the use of algorithms and software to automate the process of building, training, and deploying machine learning models. This means that even users with little to no experience in data science and machine learning can easily create and use their own machine-learning models. Low-code machine learning, on the other hand, refers to the use of user-friendly, drag-and-drop interfaces and other tools that make it easy for users to build and deploy machine learning models without writing complex code. This approach to machine learning is designed to make it easier for non-technical users, such as business analysts and domain experts, to create and use machine learning models, and to accelerate the development and deployment of machine learning applications. Both auto ML and low-code machine learning are likely to continue to grow and evolve in the coming years and are expected to have a significant impact on the field of machine learning and on the broader field of artificial intelligence. In this article, we will explore the trends and developments in auto ML and low-code machine learning, and discuss their potential impacts and implications.
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2022
If you’d like to learn more about Auto ML and Low Code ML, we encourage you to read the article above. It provides a detailed overview of these technologies and how they can be used to build and deploy machine learning models with minimal coding knowledge. Whether you’re a data scientist, developer, or non-technical user, this article will help you understand the benefits and limitations of Auto ML and Low Code ML, and how you can use these tools to solve real-world business problems. So if you’re interested in learning more about how to leverage the power of machine learning and data analysis in your organization, be sure to give the article above a read.
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