Loading…

Deep learning on edge computing devices : design challenges of algorithm and architecture /

Bibliographic Details
Call Number:	Libro Electrónico
Main Authors:	Zhou, Xichuan (Author), Liu, Haijun (Author), Shi, Cong (Author), Liu, Ji (Author)
Format:	Electronic eBook
Language:	Inglés
Published:	Amsterdam ; Cambridge, MA : Elsevier, [2022]
Subjects:	Deep learning (Machine learning) Edge computing. Apprentissage profond. Edge computing
Online Access:	Texto completo

Similar Items

Deep learning /
Published: (2023)

Deep learning for medical applications with uniue data /
Published: (2022)

Deep learning with relational logic representations /
by: Šír, Gustav
Published: (2022)

Essential tools for deep learning and data science.
Published: (2020)

Hands-on deep learning model training with the sequential API in Keras.
Published: (2020)

Deep Learning avec Keras et TensorFlow
by: Géron, Aurélien
Published: (2020)

End-to-end deep learning for predicting Airbnb prices /
Published: (2020)

Deep Learning avec Keras et TensorFlow
by: Géron, Aurélien
Published: (2020)

Training Ludwig declarative deep learning models using Mac Studio M1Ultra.
Published: (2022)

Modern deep learning design and application development : versatile tools to solve deep learning problems /
by: Ye, Andre
Published: (2022)

Deep learning : crash course 2023.
Published: (2023)

Explainable deep learning AI : methods and challenges /
Published: (2023)

Deep learning : computer vision for beginners using PyTorch.
Published: (2023)

Deep learning patterns and practices /
by: Ferlitsch, Andrew
Published: (2021)

Fundamentals of neural networks.
Published: (2022)

Deep learning CNN : convolutional neural networks with Python.
Published: (2022)

Python for deep learning : build neural networks in Python.
Published: (2022)

Deep learning : a visual approach /
by: Glassner, Andrew S.
Published: (2021)

Seisei deep learning : e o egaki, monogari o tsukuri, gēmu o pureisuru /
by: Foster, David (Business consultant)
Published: (2020)

DATA AUGMENTATION WITH PYTHON enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data /
by: Haba, Duc
Published: (2023)

Inside deep learning : math, algorithms, models /
by: Raff, Edward
Published: (2022)

Understanding Horovod for distributed gradient descent in PyTorch.
Published: (2020)

THE REGULARIZATION COOKBOOK explore practical recipes to improve the functionality of your ML models /
by: Vandenbussche, Vincent
Published: (2023)

Deep learning in personalized healthcare and decision support /
Published: (2023)

Advanced analytics and deep learning models /
Published: (2022)

Automated deep learning using neural network intelligence : develop and design PyTorch and TensorFlow models using Python /
by: Gridin, Ivan
Published: (2022)

Learn to setup Mac M1 with Tensorflow Metal /
Published: (2022)

Kyōka gakushū hen /
by: Saitō, Kōki, 1984-
Published: (2022)

Brain-computer interface : using deep learning applications /
Published: (2023)

Deep learning : deep neural network for beginners using Python.
Published: (2023)

Evolutionary deep learning : genetic algorithms and neural networks /
by: Lanham, Micheal
Published: (2023)

Neural Search, from Prototype to Production with Jina Build Deep Learning-Powered Search Systems That You Can Deploy and Manage with Ease /
by: Wang, Bo (Artificial intelligence scientist), et al.
Published: (2022)

Computational methods and deep learning for ophthalmology /
Published: (2023)

Deep learning techniques for biomedical and health informatics /
Published: (2020)

Python de manabu dīpu rāningu no riron to jissō /
by: Saitō, Kōki, 1984-
Published: (2016)

Deep learning-based forward modeling and inversion techniques for computational physics problems /
by: Wang, Yinpeng, 1999-, et al.
Published: (2024)

Machine learning y deep learning : usando Python, Scikit y Keras /
by: Bobadilla Sancho, Jesús
Published: (2020)

Artificial intelligence and machine learning for edge computing /
Published: (2022)

Applying the idiomatic design pattern to convolutional neural networks /
Published: (2020)

PyTorch to fastai de hajimeru dīpu rāningu : enjinia no tame no AI apurikēshon kaihatsu /
by: Howard, Jeremy (Scientist), et al.
Published: (2021)