BOOKS - PROGRAMMING - Trends in Deep Learning Methodologies Algorithms, Applications,...
Trends in Deep Learning Methodologies Algorithms, Applications, and Systems (Hybrid Computational Intelligence for Pattern Analysis and Understanding) - Vincenzo Piuri (Editor), Sandeep Raj (Editor), Angelo Genovese (Editor), Rajshree Srivastava (Editor) 2020 EPUB Academic Press BOOKS PROGRAMMING
ECO~14 kg CO²

1 TON

Views
23432

Telegram
 
Trends in Deep Learning Methodologies Algorithms, Applications, and Systems (Hybrid Computational Intelligence for Pattern Analysis and Understanding)
Author: Vincenzo Piuri (Editor), Sandeep Raj (Editor), Angelo Genovese (Editor), Rajshree Srivastava (Editor)
Year: 2020
Pages: 294
Format: EPUB
File size: 48.3 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Federated Learning From Algorithms to System Implementation
Machine Learning Algorithms From Scratch with Python
Metaheuristics for Machine Learning Algorithms and Applications
Applied Learning Algorithms for Intelligent IoT
Learning Algorithms Through Programming and Puzzle Solving
Understanding Machine Learning From Theory to Algorithms
Metaheuristics for Machine Learning Algorithms and Applications
Situating Language Learning Strategy Use: Present Issues and Future Trends
A Brief Introduction to Machine Learning for Engineers (Foundations and Trends(r) in Signal Processing)
Machine Learning For Beginners Step-by-Step Guide to Machine Learning, a Beginners Approach to Artificial Intelligence, Big Data, Basic Python Algorithms, and Techniques for Business (Practical Exampl
Machine Learning Algorithms Using Scikit and TensorFlow Environments
The Comprehensive Guide to Machine Learning Algorithms and Techniques
The Comprehensive Guide to Machine Learning Algorithms and Techniques
Machine Learning Algorithms in Depth (Final Release)
Machine Learning Algorithms Using Scikit and TensorFlow Environments
Machine Learning Refined Foundations, Algorithms, and Applications
Machine Learning Algorithms in Depth (Final Release)
Introduction to Algorithms for Data Mining and Machine Learning
Easily Practical Machine Learning Algorithms with Python
Learning to Write Effectively: Current Trends in European Research (Studies in Writing)
Machine Learning Step-by-Step Guide To Implement Machine Learning Algorithms with Python
Learning Algorithms A Programmer|s Guide to Writing Better Code
Advanced Computer Science Applications Recent Trends in AI, Machine Learning, and Network Security
Easy Learning Data Structures & Algorithms C++ Graphic Data Structures & Algorithms
Deep Learning
Learning Algorithms A Programmer’s Guide to Writing Better Code (Early Release)
Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Bioinformatics Algorithms an Active Learning Approach, Vol. 2 (2nd edition)
Bioinformatics Algorithms an Active Learning Approach, Vol. 1 (2nd edition)
Computer Vision Principles, Algorithms, Applications, Learning 5th Edition
Vectorization A Practical Guide to Efficient Implementations of Machine Learning Algorithms
Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification
Machine Learning Refined Foundations, Algorithms and Applications. 2nd Edition
Machine Learning Safety (Artificial Intelligence: Foundations, Theory, and Algorithms)
Interpretability in Deep Learning
Math for Deep Learning
Understanding Deep Learning
Deep Learning with Python
Understanding Deep Learning
The Deep Learning Revolution