Treffer 1 - 20 von 285

1

Introduction to Deep-Learning Concepts and TensorFlow
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow 2.0 : A Mathematical Approach to Advanced Artificial Intelligence in Python. :109-197

E-Book
3

Mathematical Foundations
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow 2.0 : A Mathematical Approach to Advanced Artificial Intelligence in Python. :1-108

E-Book
4

Natural Language Processing
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow 2.0 : A Mathematical Approach to Advanced Artificial Intelligence in Python. :293-405

E-Book
5

Advanced Neural Networks
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow 2.0 : A Mathematical Approach to Advanced Artificial Intelligence in Python. :511-634

E-Book
6

Convolutional Neural Networks
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow 2.0 : A Mathematical Approach to Advanced Artificial Intelligence in Python. :199-291

E-Book
7

Unsupervised Learning with Restricted Boltzmann Machines and Autoencoders
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow 2.0 : A Mathematical Approach to Advanced Artificial Intelligence in Python. :407-510

E-Book
8

Introduction to Deep-Learning Concepts and TensorFlow
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow : A Mathematical Approach to Advanced Artificial Intelligence in Python. :89-152

E-Book
9

A Study on the Battery Usage of Deep Learning Frameworks on iOS Devices
Jacques, Vitor Maciel Fontes ; Alizadeh, Negar ; Castor, Fernando
Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems. :1-11

Konferenz
10

Mathematical Foundations
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow : A Mathematical Approach to Advanced Artificial Intelligence in Python. :1-87

E-Book
11

Advanced Neural Networks
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow : A Mathematical Approach to Advanced Artificial Intelligence in Python. :345-392

E-Book
13

Unsupervised Learning with Restricted Boltzmann Machines and Auto-encoders
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow : A Mathematical Approach to Advanced Artificial Intelligence in Python. :279-343

E-Book
14

Convolutional Neural Networks
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow : A Mathematical Approach to Advanced Artificial Intelligence in Python. :153-221

E-Book
15

Natural Language Processing Using Recurrent Neural Networks
Pattanayak, Santanu ; Pattanayak, Santanu
Pro Deep Learning with TensorFlow : A Mathematical Approach to Advanced Artificial Intelligence in Python. :223-278

E-Book
16

Pros and Cons of Executable Neural Networks for Deeply Embedded Systems
Ferraz, Matheus Fellype ; Friesel, Birte Kristina ; Spinczyk, Olaf
Proceedings of the 2023 Workshop on Compilers, Deployment, and Tooling for Edge AI. :16-20

Konferenz
17

A Study on the Battery Usage of Deep Learning Frameworks on iOS Devices
Jacques, Vitor ; Alizadeh, Negar ; Castor, Fernando
2024 IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft) MOBILESOFT Mobile Software Engineering and Systems (MOBILESoft), 2024 IEEE/ACM 11th International Conference on. :1-11 Apr, 2024

Konferenz
18

Enhancing Cyclone Intensity Prediction Using Deep Learning Models with INSAT- 3D IR Imagery
Vikkurty, Sireesha ; Hegde, Nagaratna P. ; Kumar, Sriperambuduri Vinay ; et al.
Proceedings of the 7th International Conference on Communications and Cyber Physical Engineering : ICCCE 2024, 28–29 Febuary, Hyderabad, India. 1466:1044-1049

E-Book
20

Comparative analysis of machine learning methodologies and technologies
Mukhitdinova Kh. Munavvarkhon
Цифровые модели и решения, Vol 4, Iss 1, Pp 78-85 (2025)

tensorflow reinforcement learning machine learning ml interpretability Economics as a science pytorch
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