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Titlebook: Beginning Mathematica and Wolfram for Data Science; Applications in Data Jalil Villalobos Alva Book 20211st edition Jalil Villalobos Alva 2

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Jatinderkumar R. Saini,Vikas S. Chomalugh equations and implement specialized functions of the Wolfram Language for the same purpose. With the use of statistical functions. The Wolfram Language is a useful tool for statistics and probability. Mathematica has the functions to perform numerical and approximate calculations for descriptive
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Atul Kumar Verma,Mahipal Jadeja,Rahul Saxena built in order to have a better understanding of its use in Mathematica through the Wolfram Language. Examples will be carried out on how to download the data from this platform through the use of the Wolfram Language as well as its representation of data in the form dataset as well as using the Qu
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Divya Hiran,Hemant Kothari,Shivoham Singhutations will be shown as well as the concept of the learning curve of the model. Later, we will see how to use the specialized functions of the Wolfram Language for machine learning such as Predict, Classify and ClusterClassify, in the case of linear regression, for logistic regression and for clus
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Ashish P. Ramdasi,S. Sathyalakshmiayers, how to use the commands for different layers, and the most common layers. We will learn how to enter data into the layers by the net port, as well as the different forms of equivalent expression of the layers. This is followed by how to distinguish different layers by their symbol. We will se
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Jalil Villalobos AlvaThe first introduction to data science using Mathematica and Wolfram.Covers very popular in-demand topics such as machine learning and neural networks.Includes freely available source code
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ICT Systems Security and Privacy Protectione define what can be included within this structure as well as the creation of lists, nested lists, arrays, vectors, and matrices. We explore how to order a list, how to assign new values, and finally how to select elements of a list depending on an established pattern.
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