This article describes the SVM algorithm, its implementation and performance evaluation using the sklearn Python module.
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This article covers the theory of Naive Bayes classification and its implementation using Python, Jupyter Notebook and AWS SageMaker Studio.
This article covers the KNN algorithm theory, its implementation using Python, and the evaluation of the results using a confusion matrix.
This article covers the Decision Tree theory, algorithm implementation, and visualization using Python and AWS SageMaker Studio.
This article covers the implementation of the Linear Regression algorithm using Python, AWS SageMaker Studio, and AWS Jupyter Notebook.
This article covers types of ML, including Supervised Learning, Unsupervised Learning, Semi-supervised Learning, and Reinforcement Learning.
This article covers Machine Learning concepts, frameworks, and AWS services that you can use to incorporate ML features into your applications
The AWS Command Line Interface (CLI) is a unified tool to manage your AWS services. With just one tool to download and configure, you can control multiple AWS services from