Cross validation is the use of various techniques to evaluate a machine learning model’s ability to generalize when processing new and unseen datasets. Generalization is
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The concept of optimization is integral to machine learning. Most machine learning models use training data to learn the relationship between input and output data.
Machine Learning Optimization – Why is it so Important? Read More »
Deep learning is a form of machine learning which aims to mimic and imitate the processes of the human brain through machine learning algorithms. The resulting
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Outlier detection is a key consideration within the development and deployment of machine learning algorithms. Models are often developed and leveraged to perform outlier detection
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Concept drift is a major consideration for ensuring the long-term accuracy of machine learning algorithms. Concept drift is a specific type of model drift, and can
Machine Learning Concept Drift – What is it and Five Steps to Deal With it Read More »
Machine learning deployment is the process of deploying a machine learning model in a live environment. The model can be deployed across a range of
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Transfer learning for machine learning is when elements of a pre-trained model are reused in a new machine learning model. If the two models are
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The four types of machine learning algorithms that we aim to explain are behind a range of technologies, whether providing predictive analytics to businesses or
Four Types of Machine Learning Algorithms Explained Read More »
Kubernetes is an open-source platform used to orchestrate and manage containers and containerized applications. It allows for the automation of key elements of container management,
What is Kubernetes? Read More »
Machine learning (ML) is a process by which a system learns from data to undergo iterative improvement without direct human control. Instead of operating on
What is Machine Learning? Read More »
