One important concept in Machine Learning is learning from evidence to infer the outcomes of interest. Evidence are usually manifested as quantifiable observations and they provide clues on the outcomes of interest. A Statistical Case Suppose we are interested in whether a person is infected with a disease. We are unable to directly…

Beyond Achieving Top Accuracy We are familiar with the idea of using machine learning to make predictions and inferences to high accuracies. This is after all a big part of what machine learning is expected to do. Interestingly and importantly, we can leverage further on machine learning models. Beyond using the model to make…

Neural Networks In Machine Learning, Neural Networks are an instrumental class of models that has wide-ranging applications. Generally, a neural network contains numerous parameters that are collectively used to infer predictions or forecasts from relevant input information. Neural networks allow us to create sophisticated relationships and answer practical questions such as: (i)…

Its importance for Machines, not just Humans. What is Transfer Learning? The concept of transfer learning lies in imparting knowledge learned for performing a task to another task that is different but similar. How is Transfer Learning Useful to Me? In the context of humans, transfer learning is crucial to our lives. Examples include: the knowledge of…

My inspiration for this article arises from infrequently hearing “neural network training is not just optimization as there is a need to prevent overfitting”. So, here I am, sipping coffee and sharing one piece of knowledge! The Construction “Neural network training is not just optimization as there is a need to prevent…

1. What is feature scaling? Feature scaling is the statistical operation of using values of features to scale themselves to smaller and similar ranges. It is widely used in data pre-processing before performing further feature engineering in machine learning and deep learning. 2. What are the methods to feature scaling? There are 3 main approaches, each consisting of its own variants, to feature…