Whenever we speak about model prediction, it is essential to comprehend prediction errors (bias and variance). There is a tradeoff between a model’s ability to minimize bias and variance. Gaining a proper understanding of these errors would help us to build accurate models and prevent the risk of overfitting and underfitting. So, let’s begin with […]
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While working on a classification problem, a regression analysis, or another data science project, bagging, and boosting algorithms can play a vital role. This article summarizes: #1 the idea of ensemble learning, introduces, #2 bagging and, #3 boosting, before a comparison is made between both methods to highlight similarities and differences. #1: Introduction and idea behind ensemble learning When we see overfitting […]
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Open-source machine learning tools have revolutionized the field of AI development, providing accessible and flexible solutions for both developers and organizations. With a wide range of open-source tools available, developers have access to a wealth of resources and the ability to collaborate with others in the community. Python, with its extensive open-source network, offers libraries […]
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