Luis Valencia

48 posts
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[Algorithms] - Logistic Regression

[Algorithms] - Logistic Regression

Logistic Regression is a Machine Learning classification algorithm that is used to predict the probability of a categorical dependent variable. In logistic regression, the dependent variable is a binary variable that contains data

Ridge, Lasso, and Polynomial Linear Regression

Ridge, Lasso, and Polynomial Linear Regression

Ridge Regression Ridge regression learns , using the same least-squares criterion but adds a penalty for large variations in parameters. The addition of a penalty parameter is called regularization. Regularization is an important concept

Feature normalization

Feature normalization

Before writing the next post about Algorithms, I thought it was important to talk first about feature normalization, as it will be relevant in almost all algorithms moving forward. Some of the algorithms

Azure Machine Learning Environments

Azure Machine Learning Environments

According to Microsoft: https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.environment.environment?view=azure-ml-py An Environment defines Python packages, environment variables, and Docker settings that are used in machine learning