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Performance Metrics for Classification in Machine learning

Using the right performance metric for the right task Model Performance evaluation is a crucial step of any machine learning workflow. Those evaluation metrics estimate if the model is ready for production or needs some parameters fine-tuning. But how to choose the appropriate metric in your classification use case? In this article, we will explain …

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When to Choose Neural Networks over Traditional Machine Learning

Deep learning works better than traditional machine learning algorithms in many cases. Difference between deep learning and machine learning: Machine learning (ML) is a subfield of AI that consists of imitating human intelligence and learning from an experience without being previously programmed. ML algorithms include traditional methods such as Linear Regression, Logistic Regression, Decision Tree, …

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Cost Function and Performance Metrics in Deep Learning

Beginners can confuse cost functions with Performance metrics. Some techniques are used When creating a deep learning model to help design the optimum neural networks architecture such as cost functions and performance/evaluation metrics. Many mistake those terms and use them interchangeably! In this article, we will explain the difference between cost functions and Performance metrics, …

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