This article explores a step-by-step approach to convert any context-free grammar to a context-free grammar in Chomsky Normal Form.
Continue readingMaximum Likelihood Estimation – finding the best Parametric Model
An intuitive explanation of what likelihood is and how maximizing it gives the best parametric model that fits the data. Few examples are also worked out in detail
Continue readingVirtual Memory related Terminology
A list of definitions of Virtual Memory related terminology
Continue readingRegular Grammars
This article discusses the concept of Regular Grammars and their equivalence with NFAs. Conversion examples included.
Continue readingGradient Descent for a Single Artificial Neuron
This article explore the derivation of the gradient descent algorithm for a single artificial neuron for the logistic activation function. Few properties of the logistic function are also discussed.
Continue readingMultiple Issue Processors
An thorough overview and comparision of Static and Dynamically scheduled superscalar processors.
Continue readingContext-Free Grammar – Formal Definition and Observations
A short primer on the formal definition of a context-free grammar followed by few observations.
Continue readingPrimer on Lambda Calculus
The basic concepts of Lambda Calculus are discussed including functions, applications, the scope of free and bound variables and the order of evaluation. Few examples are worked out.
Continue readingHidden Markov Models Training – The Forward-Backward Algorithm
This article discusses the problem of learning the HMM parameters given an observation sequence and the set of possible states. The concept of backward Probability is defined and an iterative algorithm for learning is presented. Derivations and diagrams are sketched out.
Continue readingProving a Language is not Regular using the Pumping Lemma – String Choices
This article explores a step by step approach to prove that a language is not regular by using a combination of Closure Properties and the Pumping Lemma.
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