BOOKS - PROGRAMMING - Demystifying Deep Learning An Introduction to the Mathematics o...
Demystifying Deep Learning An Introduction to the Mathematics of Neural Networks - Douglas J. Santry 2024 PDF Wiley-IEEE Press BOOKS PROGRAMMING
ECO~14 kg CO²

1 TON

Views
91672

Telegram
 
Demystifying Deep Learning An Introduction to the Mathematics of Neural Networks
Author: Douglas J. Santry
Year: 2024
Pages: 259
Format: PDF
File size: 10.1 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Deep Learning for Natural Language Processing (MEAP Edition) +code
Deep Learning Illustrated A Visual, Interactive Guide to Artificial Intelligence
Toward Artificial General Intelligence: Deep Learning, Neural Networks, Generative AI
Probabilistic Machine Learning An Introduction
A hands-on introduction to machine learning
Machine Learning a Concise Introduction
An Introduction to Machine Learning Interpretability
Introduction to Statistical Relational Learning
Introduction to Cinematography Learning Through Practice
Reinforcement Learning An Introduction, 2 edition
An Introduction to Sociolinguistics (Learning about Language)
A Concise Introduction to Machine Learning
Deep Learning for Medical Image Analysis (The MICCAI Society book Series)
Real-World Natural Language Processing Practical applications with deep learning
Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics
Deep Learning Concepts and Applications for Beginners Guide to Building Intelligent Systems
Deep Learning: A Practitioner|s Approach by Josh Patterson, O|Reilly Media
Deep Learning Applications in Medical Image Segmentation Overview, Approaches, and Challenges
Deep Learning at Scale At the Intersection of Hardware, Software, and Data (Third Early Release)
Deep Learning Theory, Architectures and Applications in Speech, Image and Language Processing
Deep Learning at Scale At the Intersection of Hardware, Software, and Data (Third Early Release)
Deep Reinforcement Learning for Wireless Communications and Networking: Theory, Applications and Implementation
Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play
Deep Learning Theory, Architectures and Applications in Speech, Image and Language Processing
Deep Learning at Scale At the Intersection of Hardware, Software, and Data (Final Release)
Deep Learning for Agricultural Visual Perception: Crop Pest and Disease Detection
Statistical Process Monitoring using Advanced Data-Driven and Deep Learning Approaches
Foundations of Deep Reinforcement Learning Theory and Practice in Python (Rough Cuts)
Generative Deep Learning Teaching Machines to Paint, Write, Compose and Play
Modern Deep Learning for Tabular Data: Novel Approaches to Common Modeling Problems
Deep Learning at Scale At the Intersection of Hardware, Software, and Data (Final Release)
Deep Learning in Medical Image Analysis Recent Advances and Future Trends
Deep Learning Concepts in Operations Research (Advances in Computational Collective Intelligence)
Deep Learning Systems Algorithms, Compilers, and Processors for Large-Scale Production
Deep Learning on Edge Computing Devices Design Challenges of Algorithm and Architecture
Deep Learning in Medical Image Analysis Recent Advances and Future Trends
AI for Data Science Artificial Intelligence Frameworks and Functionality for Deep Learning, Optimization, and Beyond
Deep Learning for Coders with fastai and PyTorch AI Applications Without a PhD (Early Release)
Deep Reinforcement Learning for Wireless Communications and Networking Theory, Applications and Implementation
Introduction to Machine Learning, 3rd Edition