## importance of probability in computer science

These techniques require assessing the data and their behaviour carefully up-front. >> Alright, sure, let's go. We're going to think about these kinds of questions and we're going to apply it to simple games. >> So this week we're going to actually look at probability. Learning of probability helps you in making informed decisions about likelihood of events, based on a pattern of collected data.. To keep the class fun and engaging, many of the projects will involve working with strategy-based games. Once we understand how the values are distributed then we can start estimating the probabilities of the events, even by the means of using formulas (known as probability distribution functions). Which variables exhibit normal distribution? You want to go double or nothing, two weeks? Joe, I wouldn't have expected that mistake from, Scott, not from you. >> Do it. >> Heads. Here we go. As the normal distribution is simple and is well-understood, it is also overused in the predictive projects. Normal distribution is a bell-shaped curve where mean=mode=median. >> Broken? But the question now, what is the probability that we will just get someone with the blue eyes just by chance. Both of these transformers have their own use cases and both work in a different manner. email: jobs@rapleaf.com. But the suspect says I saw that, that the witness says I saw that the suspect has blue eyes. [LAUGH] No problem, right. If I remember correctly, I don’t think it was even specifically required, although it was an option that meet a requirement. Each sample has its own mean. What is so special about normal probability distribution? The probability distribution is dependent on the moments of the sample such as mean, standard deviation, skewness, and/or kurtosis. A unique probability guide for computer science While many computer science curricula include only an introductory course on general probability, there is a recognized need for further study of this mathematical discipline within the specific context of computer science. Some believe that it adds only little value in Computer Science while others (mostly in the majority!) Consequently, if a value cannot occur then it is assigned a probability of 0%. >> [LAUGH] >> [UNKNOWN] has nothing to do with the first three times. Part of the problem is that statistics pedagogy is weak, particularly at the introductory level — perhaps especially as perceived by engineering students. This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course. Use Of Probability Concepts of probability have been given an axiomatic mathematical formalization in probability theory which is used widely in such areas of study as mathematics, statics, finance, gambling, science (in particular physics), artificial intelligence/machine learning, computer science, game theory, and philosophy. Assuming normality has its own flaws. There's a lot of interesting applications of probability in computer science. In the context of data science, statistical inferences are often used to analyze or predict trends from data, and these inferences use probability distributions of data. Probability quantifies the likelihood or belief that an event will occur. Estimates and predictions form an important part of Data science. Explanation of power transformers such as Box-Cox and Yeo Johnson and their use-cases is beyond the scope of this article. >> So either you or I are going to have to grade all the mini projects this week. I too was surprised by how little math/stat was required for computer science major. So, it is 1/2 that you see a head, 1/2 that you see a tail. Lou, do you want to give us some examples of where we might actually use probability in a more practical setting? >> Let's see. Distributed training of Deep Learning models with PyTorch, Categorical Encoding: Label Encoding & One-Hot Encoding, Off-policy policy gradient reinforcement learning algorithms, Training Cutting-Edge Neural Networks with Tensor2Tensor and 10 lines of code, Explainable AI: From Prediction To Understanding, How to Train Your First Deep Learning Model. To view this video please enable JavaScript, and consider upgrading to a web browser that. The independent random variables that exhibit normal distribution always exhibit a normal distribution. >> Like all 10,000 of them? I don’t know but I’m taking a 300 level probability math course that is required by my university’s CS program. And then the witness comes and says something about the suspect. In this course we study applications of probabilistic techniques to computer science, focusing on randomised algorithms and the probabilistic analysis of algorithms. Algorithms for search results, matching, and more rely on probability. Second 50/50. This curve is known as the probability distribution curve and the likelihood of the target variable getting a value is the probability distribution of the variable. >> Yeah, yeah. There are a large number of probability distributions and the most widely used probability distribution is known as “normal distribution”. So, now what is the probability that the person has blue eyes, and blonde hair? The center of the curve has the most number of points. There is an equal number of points on each side of the curve. Rarely is this explained. The following discussion explains it further: i. If we plot the probability distribution and it forms a bell-shaped curve and the mean, mode, and median of the sample are equal then the variable has normal distribution. This article illustrates what normal distribution is and why it is widely used, in particular for a data scientist and a machine learning expert. [MUSIC]. The higher the probability, the more likely it is for the event to occur. Imagine the confidence data scientists now have when making future decisions once they understand the probability distribution of a target variable. it will likely become on the most important classes in the future. Probabilities as one of the key components of the courseb we did skip list when we were doing a data structure classvand now I’m gonna take a formal Math course really offered by Math Department on probability theory, We have Probability and Statistics as a compulsory course in the Computer Science faculty, University of Perugia, Italy. >> So this week, we're going to just look at games like this, but we want you to keep this in mind.

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