Mastering the Basics Part 13: Understanding of Statistics and Probability for Data and AI

<p>Probability provides the mathematical foundation to model uncertainty, make predictions, evaluate models, and make data-driven decisions in the dynamic and often uncertain environments where AI and data science are applied. Concepts from probability are applied in various contexts, including data analysis, decision-making, and modeling in AI and machine learning.</p> <p><img alt="" src="https://miro.medium.com/v2/resize:fit:700/1*9SHAULi-SvEyKIvF8iaHsw.png" style="height:400px; width:700px" /></p> <p>Below are the several concepts used when it comes to data science and AI:</p> <p><strong>Probability Distributions:</strong>&nbsp;Understanding different types of probability distributions (e.g., normal, binomial, Poisson) is essential for modeling and analyzing data. These distributions help in understanding the likelihood of different outcomes.</p> <p><a href="https://medium.com/@curiousmind1786/mastering-the-basics-part-13-understanding-of-statistics-and-probability-for-data-and-ai-b543263bbf41"><strong>Website</strong></a></p>
Tags: Data AI