















\""Simplified Machine Learning\"" is a comprehensive guide that navigates readers through the intricate landscape of Machine Learning, offering a balanced blend of theory, algorithms, and practical applications. The first section introduces foundational concepts such as supervised and unsupervised learning, regression, classification, clustering, and feature engineering, providing a solid base in Machine Learning theory. The second section explores algorithms like decision trees, support vector machines, and neural networks, explaining their functions, strengths, and limitations, with a special focus on deep learning, reinforcement learning, and ensemble methods. The book also covers essential topics like model evaluation, hyperparameter tuning, and model interpretability. The final section
Simplified Machine Learning
The essential building blocks for Machine Learning expertise (English Edition)
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Details:\""Simplified Machine Learning\"" is a comprehensive guide that navigates readers through the intricate landscape of Machine Learning, offering a balanced blend of theory, algorithms, and practical applications. The first section introduces foundational concepts such as supervised and unsupervised learning, regression, classification, clustering, and feature engineering, providing a solid base in Machine Learning theory. The second section explores algorithms like decision trees, support vector machines, and neural networks, explaining their functions, strengths, and limitations, with a special focus on deep learning, reinforcement learning, and ensemble methods. The book also covers essential topics like model evaluation, hyperparameter tuning, and model interpretability. The final section
Simplified Machine Learning
The essential building blocks for Machine Learning expertise (English Edition)
Free UK delivery on this item.
This brand new item is available with free UK delive;
Price now:
From
To
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\""Simplified Machine Learning\"" is a comprehensive guide that navigates readers through the intricate landscape of Machine Learning, offering a balanced blend of theory, algorithms, and practical applications. The first section introduces foundational concepts such as supervised and unsupervised learning, regression, classification, clustering, and feature engineering, providing a solid base in Machine Learning theory. The second section explores algorithms like decision trees, support vector machines, and neural networks, explaining their functions, strengths, and limitations, with a special focus on deep learning, reinforcement learning, and ensemble methods. The book also covers essential topics like model evaluation, hyperparameter tuning, and model interpretability. The final section
Simplified Machine Learning
The essential building blocks for Machine Learning expertise (English Edition)
Free UK delivery on this item.
This brand new item is available with free UK delive;
General | |
|---|---|
Brand | De Gruyter |
format | ebook |
Language | english |
type | textbook |
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