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Deep learning with PyTorchStevens, Eli ; Antiga, Luca ; Viehmann, ThomasDeep Learning with PyTorch teaches you to create neural networks and deep learning systems with PyTorch. This practical book quickly gets you to work building a real-world example from scratch: a ... tumor image classifier. Along the way, it covers best practices for the entire DL pipeline, including the PyTorch Tensor API, loading data in Python, monitoring training, and visualizing results. After covering the basics, the book will take you on a journey through larger projects. The centerpiece of the book is a neural network designed for cancer detection. You'll discover ways for training networks with limited inputs and start processing data to get some results. You'll sift through the unreliable initial results and focus on how to diagnose and fix the problems in your neural network. Finally, you'll look at ways to improve your results by training with augmented data, make improvements to the model architecture, and perform other fine tuningVrsta gradiva - knjigaZaložništvo in izdelava - Shelter Island (NY) : Manning, cop. 2020Jezik - angleškiISBN - 978-1-61729-526-3; 1-617-29526-4COBISS.SI-ID - 59223299
Avtor
Stevens, Eli |
Antiga, Luca |
Viehmann, Thomas
Drugi avtorji
Chintala, Soumith
Teme
Neural networks (Computer science) |
Machine learning |
Artificial intelligence |
Python (Computer program language) |
Python (Computer program language) |
Neural networks (Computer science) |
Artificial intelligence |
Machine learning |
Instructional and educational works |
Instructional and educational works |
globoko učenje |
PyTorch |
strojno učenje |
nevronske mreže |
umetna inteligenca |
Python |
Python
Signatura – lokacija, inventarna št. ... |
Status izvoda | Rezervacija |
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Inštitut za antropološke in prostorske študije 0000210605 IN: 8162127 Inštitut za antropološke in prostorske študije 210605 IN: 8162127 |
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Stevens, Eli | |
Antiga, Luca | |
Viehmann, Thomas | |
Chintala, Soumith |
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