<i>Introduction to Deep Learning and Neural Networks with PythonT: A Practical Guide</i> is an intensive step-by-step guide for neuroscientists to fully understand, practice, and build neural networks. Providing math and PythonT code examples to clarify neural network calculations, by book''s end readers will fully understand how neural networks work starting from the simplest model Y=X and building from scratch. Details and explanations are provided on how a generic gradient descent algorithm works based on mathematical and PythonT examples, teaching you how to use the gradient descent algorithm to manually perform all calculations in both the forward and backward passes of training a neural network. <br><br><ul><li>Examines the practical side of deep learning and neural networks</li><li>Provides a problem-based approach to building artificial neural networks using real data</li><li>Describes PythonT functions and features for neuroscientists</li><li>Uses a careful tutorial approach t
Pris: kr 1479.00 fra Norli
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<i>Python Programming and Numerical Methods: A Guide for Engineers and Scientists</i> introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational...
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Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the...
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Transition to Nursing Practice: From Student to Professional provides students with a comprehensive introduction into the nursing profession and the capabilities they need for practice.Written by experts in their field, the text takes an evidence-based...
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