Tag: Min-Max Scaling
Running ML on raw, unprocessed data
Running machine learning (ML) on raw, unprocessed data is a critical yet intricate process that forms the backbone of any successful ML project. This comprehensive guide delves into each step….
Ignoring community modules’ security risks
Ignoring Community Modules’ Security Risks: Understanding the Importance of Secure IaC Practices Introduction Infrastructure as Code (IaC) is one of the cornerstones of modern DevOps practices, enabling teams to automate….
Running conflicting IaC deployments
Running Conflicting IaC Deployments: Understanding the Challenges and Best Practices Introduction Infrastructure as Code (IaC) has become the foundation for modern DevOps practices, allowing teams to define, provision, and manage….
Not normalizing data before training ML models
Data normalization is a crucial preprocessing step in machine learning. If skipped, it can negatively affect model performance, particularly for algorithms that rely on feature scaling. In this guide, I….
Feature Scaling in Machine Learning
Feature Scaling in Machine Learning Introduction Feature scaling is a crucial step in the data preprocessing stage of machine learning. It ensures that all numerical features in the dataset have….
Feature Engineering
Feature Engineering: A Comprehensive Guide Introduction Feature engineering is the process of transforming raw data into meaningful features that improve the performance of machine learning models. It involves selecting, creating,….
Data Normalization and Standardization
Data Normalization and Standardization: A Comprehensive Guide Introduction Data preprocessing is a crucial step in machine learning, and normalization and standardization are two fundamental techniques used to rescale data. These….