Many companies are using data to drive their decisions. The aim is to remove uncertainties, guesswork, and gut feeling. A/B testing is a methodology that can be applied to validate a hypothesis and steer the decisions in the right direction. In this blog post, I want to show how to create a containerized micro-service architecture […]
A practical guide to A/B Testing in MLOps with Kubernetes and Seldon Core Read More »
Machine learning model inference is the use of a machine learning model to process live input data to produce an output. It occurs during the machine learning deployment phase of the machine learning model pipeline, after the model has been successfully trained. Machine learning model inference can be understood as making a model operational, or
Machine Learning Model Inference vs Machine Learning Training Read More »
Machine learning optimization is an important part of all machine learning models. Whether used to classify an image in facial recognition software or cluster users into like-minded customer groups, all types of machine learning model will have undergone a process of optimization. In fact, machine learning itself can be described as solving an optimization problem,
Algorithm Optimization for Machine Learning Read More »
Artificial neural network models are behind many of the most complex applications of machine learning. Classification, regression problems, and sentiment analysis are some of the ways artificial neural networks are being leveraged today. As an emerging field, there are many different types of artificial neural networks. They vary for a variety of reasons, such as
Neural Network Models Explained Read More »
How to Deploy Models on Kubernetes Kubernetes is a container orchestration platform used to manage containerized applications. It used to automate important parts of the container management process such as container replication, scaling, monitoring and scheduling. It’s an open-source platform written in Google’s Go programming language. Kubernetes is one of the most popular container management
A Guide to Deploying Machine Learning Models on Kubernetes Read More »
Decision trees in machine learning are a common way of representing the decision-making process through a branching, tree-like structure. It’s often used to plan and plot business and operational decisions as a visual flowchart. The approach sees a branching of decisions which end at outcomes, resulting in a tree-like structure or visualization. Decision trees
Decision Trees in Machine Learning Explained Read More »
Machine Learning Regression is a technique for investigating the relationship between independent variables or features and a dependent variable or outcome. It’s used as a method for predictive modeling in machine learning, in which an algorithm is used to predict continuous outcomes. Solving regression problems is one of the most common applications for machine learning
Machine Learning Regression Explained Read More »
AI Bias appears in machine learning in lots of different forms and in a world that is increasingly becoming more reliant on this type of technology, it’s important to understand the most common types of bias. But as a place to start, the important thing to consider is that training a machine learning model is
Six Types of AI Bias Everyone Should Know Read More »
Machine learning is becoming integral to how the modern world functions, with more and more sectors harnessing the power of algorithms to automate tasks and make decisions. As machine learning models become ingrained within decision-making processes for a range of organizations, the topic of bias in machine learning is an important consideration. The aim for
Machine Learning Bias and Fairness Read More »
Covariate shift is a specific type of dataset shift often encountered in machine learning. It is when the distribution of input data shifts between the training environment and live environment. Although the input distribution may change, the output distribution or labels remain the same. Covariate shift is also known as covariate drift, and is a very
What is Covariate Shift? Read More »
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