Showing 141 - 160 of 324

141

Learn Python in 7 Days
Mohit ; Das, Bhaskar N. ; Mohit ; et al.

Electronic Resource
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142

A Simple Function
de Groot, Coen
Python Functions Deep Dive Part 1 ; ISBN 9798868801600

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143

What and Why
de Groot, Coen
Python Functions Deep Dive Part 1 ; ISBN 9798868801600

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144

Learn Python in 7 Days
Das, Bhaskar N. ; Das, Bhaskar N. ; Mohit ; et al.

Electronic Resource
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145

Return Values
de Groot, Coen
Python Functions Deep Dive Part 1 ; ISBN 9798868801600

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146

Fixture factories for faster end-to-end tests
Stephan Jaensch ; Kompetenzzentrum für nicht-textuelle Materialien

Computer Science Studienbereich Informati... Ingenieurwissenschaften
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147

Building RESTful Python Web Services
Hillar, Gaston C. ; Hillar, Gaston C. ; Hillar, Gaston C. ; et al.

Electronic Resource
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148

Why, Where, What and How to contribute to OpenStack
Thierry Carrez ; Kompetenzzentrum für nicht-textuelle Materialien

Computer Science Studienbereich Informati... Ingenieurwissenschaften
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149

Deep learning with TensorFlow and Keras: build and deploy supervised,. unsupervised, deep, and reinforcement learning mod. Expert insight.
Kapoor Amita ; Gulli Antonio ; Pal Sujit ; et al.
EN05CEBSCO05C5

Machine learning Artificial intelligence Neural networks (Compute... Python (Computer program...
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150

PySDR: A Guide to SDR and DSP using Python: And my Experience Teaching CS students DSP + SDR
Marc Lichtman ; Kompetenzzentrum für nicht-textuelle Materialien

Computer Science Studienbereich Informati... Ingenieurwissenschaften
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151

FEATURES OF THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE FORMATION OF CREATIVITY IN THE PROFESSIONAL TRAINING OF TEACHERS
Kyslitsyn, Vitalii ; Liubarska, Liudmyla ; Ostapovets, Anatolii ; et al.
ENVIRONMENT. TECHNOLOGY. RESOURCES. Proceedings of the International Scientific and Practical Conference; Vol. 3 (2025): Environment. Technology. Resources. Proceedings of the 16th International Scientific and Practical Conference. Volume 3; 203-211 ; 2256-070X ; 1691-5402

artificial intelligence innovative tools and tec... creativity professional training hybrid learning pedagogical technologies
Academic journal
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152

Learning BeagleBone Python Programming
Hiam, Alexander ; Hiam, Alexander ; Hiam, Alexander ; et al.

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153

Varijante gradijentnog spusta u strojnom učenju s primjerima ; Variants of gradient descent in machine learning with examples
Bošnjak, Dorotea ; Sandrić, Nikola

konvergencija gradijentn... metode ubrzanja optimizacijski algoritmi Python gradient descent converg... acceleration methods
Dissertation/ Thesis
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154

Profiling the unprofilable
Dmitry Trofimov ; Kompetenzzentrum für nicht-textuelle Materialien

Computer Science Studienbereich Informati... Ingenieurwissenschaften
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155

Machine Learning Engineering with Python
Andrew P. McMahon ; Adi Polak ; Andrew P. McMahon ; et al.
2023

Electronic Resource
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156

Fundamentals of Computational Neuroscience ; Third Edition
Trappenberg, Thomas P.
ISBN 0192869361 9780192869364 9780191965418.

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157

GIS++: Modern C++ for Efficient and Parallel In-Memory Spatial Computing
Martin Werner
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Geospatial Data Access and Processing APIs. :1-2

11. Sustainability 15. Life on land 16. Peace & justice 7. Clean energy
Academic journal
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158

Getting Started with TensorFlow
Zaccone, Giancarlo ; Zaccone, Giancarlo ; Zaccone, Giancarlo ; et al.

Electronic Resource
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159

Herramienta de ayuda diagnóstica basada en redes neuronales para analizar angiogramas reticulares implementada en el Instituto para Niños Ciegos y Sordos
Gómez Réndon, Mario Andrés ; López Sotelo, Jesús Alfonso ; González Vargas, Andrés Mauricio
instname:Universidad Autónoma de Occidente ; reponame:Repositorio Institucional UAO ; [1] Verdejo, D. L. (2014). Angiografía con fluoresceína. SOCV Sociedad Oftalmológica de La Comunidad Valenciana. Recuperado de: http://www.socv.org/angiografia-con-fluoresceina/ [2] E. Hosseini-Asl, Hosseini-Asl, E., Keynto, R., & El-Baz, A. (2016). Alzheimer’s Disease Diagnostics by Adaptation of 3D Convolutional Network, (Icip). https://doi.org/10.1109/ICIP.2016.7532332, 1st ed. Luoisville, 2016. [3] C. Gonzales, propósitos y metodología de la sistematización, 1st ed. Facultad Nacional De Salud Pública, 2015.[En línea]. Disponible en: http://www.udea.edu.co/wps/wcm/connect/udea/2e43da6b-2db8-43f5-95faa3026ade8d77/PROP%C3%93SITOS+Y+METODOLOG%C3%8DA+DE+LA+SIS TEMATIZACI%C3%93N.pdf?MOD=AJPERES [4] Lahiri, A., Roy, A. G., Sheet, D., & Biswas, P. K. (2016). Deep neural ensemble for retinal vessel segmentation in fundus images towards ....

Ingeniería Biomédica Redes neurales (Computad... Angiografía reticular Neural networks (Compute... Angiography
Dissertation/ Thesis
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160

DEEP LEARNING AND AI WITH PYTHON: THE NEXT-GEN REVOLUTION
Dr. SREENIVASULU GOGULA ; Dr. NIKHILA KATHIRISETTY ; FARHANA BEGUM ; et al.

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