Explaining Bayes’ Theorem with an Owambe

bayesian owambe

Bayes Theorem is an important approach in statistics for testing hypotheses and deriving estimates. According to Wikipedia: Bayes’ theorem (alternatively Bayes’ law or Bayes’ rule, also written as Bayes’s theorem) describes the probability of an event, based on prior knowledge of conditions that might be related to the event. For example, if cancer is related to age, then, using Bayes’ theorem, a person’s … Read more Explaining Bayes’ Theorem with an Owambe

Introduction to Neural Networks – Part 2

From the previous post we explained what the neural network is and what it does. A neural network consists of a input layer, hidden layer (middle layer) and the output layer. The input layer takes in the input (images, files, audio, video etc), passes it to the hidden layer where come processing/learning is done and passed … Read more Introduction to Neural Networks – Part 2

Introduction to Neural Networks – Part 1

What are neural networks? Humans can easily identify objects because the brain has “seen” (learned) the images of those objects before – as input, processes it and then identifies the object as a dog, book, stick e.t.c. However, this is extremely difficult for computers. Why? Because computers are primarily programmed for computational results. Computers compute! … Read more Introduction to Neural Networks – Part 1