Bayesian network is a model used for studying different statistical information based on conditional probabilities. The model consists of nodes and edges, forming a tree that is important for establishing a conditional connection between all the nodes. Click to know more!
Programming and mathematics go hand-in-hand. Eventually, every programming problem is an underlying mathematics problem where programming has been used simply as a tool to perform computation and obtain the output. Click to know more about coding math!
The Bayes theorem helps the AI robotic structures to auto-update their memory and their intelligence. This, in turn, makes the predictions more accurate and a practical application of this conditional probability is established. Click to know more about Bayesian logic in artificial intelligence!
Bayesian Analysis finds great use in mathematics. It is used to answer many research questions about unknown parameters by using probability. Click to learn more about Bayesian analysis!
Bayesian inference is a strong collection of tools for modelling any arbitrary variable, for example, the estimation of a regression parameter, a business KPI, a demographic statistic, or the grammatical feature of a word. Click to know more!
Conditional Probability is an important component of learning Statistics, which is important to learn Machine Learning and Artificial Intelligence. Click to learn how to use conditional probability!
Bayes Rule is one of the most important theorems of Probability, and lies in the heart of it. Click to learn more about the Bayes Rule!
If you want to become a data scientist, having at least basic understanding of statistics is mandatory. Click to know the basic statistics for data science!
R is a widely used open-source system for statistical analysis, and statistical programming. Click to know more about R statistics!