Titlebook: Deep Learning Models; A Practical Approach Jonah Gamba Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license t

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Remote Sensing Example for Deep Learning,sification starting from a?known dataset. Although we use remote sensing as an example, the key point is to show the level of hyper-parameter tuning required to get desired results from any multiclass problem to which deep learning is applied. To emphasize the hands-on approach the full script is pr

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Xiaocun Zhu,Pius Leuba dit Gallandrted for deep learning model evaluation, both offline and online. Finally, some self-evaluation exercises are given to emphasize the key takeaways from the chapter. We also provide a?list of references for further reading.

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Amaresh Chakrabarti,Vishal Singhsification starting from a?known dataset. Although we use remote sensing as an example, the key point is to show the level of hyper-parameter tuning required to get desired results from any multiclass problem to which deep learning is applied. To emphasize the hands-on approach the full script is pr

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2730-7484 p learning is employed. By consolidating all necessary information into a single resource, readers can bypass the hassle of scouring scattered online sources, gaining a one-stop solution to dive into deep learn978-981-99-9674-2978-981-99-9672-8Series ISSN 2730-7484 Series E-ISSN 2730-7492

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Building Deep Learning Models,of the concepts behind these models are briefly explained so as to give the reader smooth entry into each section while concentrating mainly of how-to-use rather than details of algorithms themselves. The entry point is shallow networks, upon which the deep neural networks are developed. The is then

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