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Weka algorithm A series of repeatable steps for carrying out a certain type of task with data. As with data structures, people studying computer science learn about different algorithms and their suitability for various tasks. Specific data structures often play a role in how certain algorithms get implemented.

AngularJS is popular with data scientists as a way to show the results of their analysis. As the cost of computing resources dropped, the focus moved more toward statistical analysis of large amounts of data to drive decision making that gives the appearance of intelligence.

See also machine learningdata mining backpropagation Also, backprop. An algorithm for iteratively adjusting the weights used in a neural network system. Backpropagation is often used to implement gradient descent. An equation for calculating the probability that something is true if something potentially related to it is true.

The theorem also makes it easier to update a probability based on new data, which makes it valuable in the many applications where data continues to accumulate. Named for eighteenth-century English statistician and Presbyterian minister Thomas Bayes. See also Bayesian networkprior distribution Bayesian network Also, Bayes net.

These graphs aid in performing reasoning or decision making in the face of uncertainty. Variance is the tendency to learn random things irrespective of the real signal Simultaneously avoiding both requires learning a perfect classifier, and short of knowing it in advance there is no single technique that will always do best no free lunch.

A key driver of this new ability has been easier distribution of storage and processing across networks of inexpensive commodity hardware using technology such as Hadoop instead of requiring larger, more powerful individual computers. The work done with these large amounts of data often draws on data science skills.

This is a discrete probability distribution, as opposed to continuous—for example, instead of graphing it with a line, you would use a histogram, because the potential outcomes are a discrete set of values. As the number of trials represented by a binomial distribution goes up, if the probability of success remains constant, the histogram bars will get thinner, and it will look more and more like a graph of normal distribution.

See also normal distribution and Wikipedia on the chi-squared test and on chi-squared distribution. Deciding whether an email message is spam or not classifies it among two categories, and analysis of data about movies might lead to classification of them among several genres.

See also supervised learningclustering clustering Any unsupervised algorithm for dividing up data instances into groups—not a predetermined set of groups, which would make this classification, but groups identified by the execution of the algorithm because of similarities that it found among the instances.

See also correlation computational linguistics Also, natural language processing, NLP. A branch of computer science for parsing text of spoken languages for example, English or Mandarin to convert it to structured data that you can use to drive program logic.

Early efforts focused on translating one language to another or accepting complete sentences as queries to databases; modern efforts often analyze documents and other data for example, tweets to extract potentially valuable information.

See also GATEUIMA confidence interval A range specified around an estimate to indicate margin of error, combined with a probability that a value will fall in that range.

The field of statistics offers specific mathematical formulas to calculate confidence intervals. For example, if you can express age or size with a decimal number, then they are continuous variables.

In a graph, the value of a continuous variable is usually expressed as a line plotted by a function. The correlation coefficient is a measure of how closely the two data sets correlate.

A correlation coefficient of 1 is a perfect correlation.

This value can also be negative, as when the incidence of a disease goes down when vaccinations go up. A correlation coefficient of -1 is a perfect negative correlation. Always remember, though, that correlation does not imply causation. The training set is given to the algorithm, along with the correct answers The algorithm is then asked to make predictions for each item in the test set.

The answers it gives are compared to the correct answers, and an overall score for how well the algorithm did is calculated. D3 is popular with data scientists as a way to present the results of their analysis.

They run ETL software, marry data sets, enrich and clean all that data that companies have been storing for years.The MATLAB codes written by me are available to use by researchers, to access the codes click on the right hand side logo.

The main focus of these codes is on the fluid dynamics simulations. algorithm. A series of repeatable steps for carrying out a certain type of task with data.

As with data structures, people studying computer science learn about . EXPRESSIONS, FUNCTIONS, AND CONSTANTS. Spice (the simulator) and Nutmeg (the front-end) data is in the form of vectors: time, voltage, nationwidesecretarial.com vector has a type, and vectors can be operated on and combined in algebraic ways consistent with their types.

Imaginary numbers always confused me. Like understanding e, most explanations fell into one of two categories. It’s a mathematical abstraction, and the equations work out. Deal with it.

It’s used in advanced physics, trust us. 2D computer graphics is the computer-based generation of digital images—mostly from two-dimensional models (such as 2D geometric models, text, and digital images) and by techniques specific to nationwidesecretarial.com word may stand for the branch of computer science that comprises such techniques or for the models themselves.

Aug 06, · Write a formula for a two-dimensional vector field which has all vectors parallel to the x-axis and all vectors on a horizontal line having the same nationwidesecretarial.com: Resolved.

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data science glossary