Data science articles related with statistic. Our Data Scientist is writing this articles.
Background The goal of this project is to generate Gaussian samples in 2-D from uniform samples, the latter of which can be readily generated using built-in random number generators in most computer languages. In part 1 of the project, the inverse transform sampling was used to convert each uniform sample into respective x and y coordinates of …
Background In part 1 of this project, I’ve shown how to generate Gaussian samples using the common technique of inversion sampling: First, we sample from the uniform distribution between 0 and 1 — green points in the below animation. These uniform samples represent the cumulative probabilities of a Gaussian distribution i.e. the area under the distribution to …
Background Gaussian sampling — that is, generating samples from a Gaussian distribution — plays an important role in many cutting-edge fields of data science, such as Gaussian process, variational autoencoder, or generative adversarial network. As a result, you often see functions like tf.random.normal in their tutorials. But, deep down, how does computer know how to generate Gaussian samples? This series …
Background In previous parts of my project, I built different n-gram models to predict the probability of each word in a given text. This probability is estimated using an n-gram — a sequence of words of length n — which contains the word. The below formula shows how the probability of the word “dream” is estimated …
