Titlebook: Machine Learning with Python; Theory and Implement Amin Zollanvari Textbook 2023 The Editor(s) (if applicable) and The Author(s), under exc

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Feature Selection,ensionality reduction is . in which a set of candidate features are transformed to a lower cardinality set of new features using some linear or non-linear mathematical transformations. Feature selection can be seen as a special type of feature extraction in which the physical nature of features are

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Assembling Various Learning Steps,alization, imputation, feature selection/extraction, model selection and training, and evaluation. The misuse of some of these steps in connection with others have been so common in various fields of study that have occasionally triggered warnings and criticism from the machine learning community. T

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Clustering, “classification” that was covered extensively in previous chapters, clustering is based on the assumption that there is no information about class labels to guide the process of grouping. In other words, clustering is an unsupervised classification of observations. Broadly speaking, “exclusive” (al

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Deep Learning with Keras-TensorFlow,ment learning. Among all family of predictive models that are used in machine learning, by deep learning we exclusively refer to a particular class of models known as multilayered Artificial Neural Network (ANN), which are partially inspired by our understanding of biological neural circuits. Genera

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ory of Machine Learning and implementation in Python.SupplemThis book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective. The choice of the topics in the book is made