The book covers concepts, techniques, and algorithms commonly used and more advanced and recent approaches with practical use. For example, you will learn to train and validate different models covering statistical methods, machine learning algorithms, and various deep learning architectures for forecasting and outlier (or anomaly) detection. Most importantly, the variety of datasets used in this book will give you a better insight into how these different models work and how you can pick the most appropriate approach to solve your specific problem.
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