BOOKS - PROGRAMMING - Deep Learning Examples with PyTorch and fastai A Developers' Co...
Deep Learning Examples with PyTorch and fastai A Developers
ECO~15 kg CO²

1 TON

Views
3104

Telegram
 
Deep Learning Examples with PyTorch and fastai A Developers' Cookbook
Author: Dr. Bernhard J. Mayr MBA
Year: 2020
Pages: 390
Format: PDF | EPUB
File size: 26 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Deep Reinforcement Learning and Its Industrial Use Cases AI for Real-World Applications
Toward Artificial General Intelligence Deep Learning, Neural Networks, Generative AI
Machine and Deep Learning Using MATLAB: Algorithms and Tools for Scientists and Engineers
Toward Artificial General Intelligence: Deep Learning, Neural Networks, Generative AI
Deep Learning Techniques and Optimization Strategies in Big Data Analytics
Deep Learning Illustrated A Visual, Interactive Guide to Artificial Intelligence
Statistical Process Monitoring using Advanced Data-Driven and Deep Learning Approaches
Modern Deep Learning for Tabular Data: Novel Approaches to Common Modeling Problems
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)
AI for Data Science Artificial Intelligence Frameworks and Functionality for Deep Learning, Optimization, and Beyond
Deep Learning for Agricultural Visual Perception: Crop Pest and Disease Detection
Generative Deep Learning Teaching Machines to Paint, Write, Compose and Play
Deep Learning: A Practitioner|s Approach by Josh Patterson, O|Reilly Media
Deep Learning Concepts in Operations Research (Advances in Computational Collective Intelligence)
Deep Learning at Scale At the Intersection of Hardware, Software, and Data (Final Release)
Deep Learning at Scale At the Intersection of Hardware, Software, and Data (Third Early Release)
Deep Learning in Medical Image Analysis Recent Advances and Future Trends
Deep Learning at Scale At the Intersection of Hardware, Software, and Data (Third Early Release)
Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play
Real-World Natural Language Processing Practical applications with deep learning
Deep Learning in Medical Image Analysis Recent Advances and Future Trends
Deep Learning Systems Algorithms, Compilers, and Processors for Large-Scale Production
Foundations of Deep Reinforcement Learning Theory and Practice in Python (Rough Cuts)
Deep Learning on Edge Computing Devices Design Challenges of Algorithm and Architecture
Deep Reinforcement Learning for Wireless Communications and Networking: Theory, Applications and Implementation
Deep Learning Concepts and Applications for Beginners Guide to Building Intelligent Systems
Deep Learning for Medical Image Analysis (The MICCAI Society book Series)
Deep Reinforcement Learning for Wireless Communications and Networking Theory, Applications and Implementation
Deep Learning Theory, Architectures and Applications in Speech, Image and Language Processing
Deep Learning Applications in Medical Image Segmentation Overview, Approaches, and Challenges
Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics
Machine Learning with Python The Ultimate Guide for Absolute Beginners with Steps to Implement Artificial Neural Networks with Real Examples (Useful Python Tools eg. Anaconda, Jupiter Notebook)
Artificial Intelligence and Brain Research Neural Networks, Deep Learning and the Future of Cognition
Artificial Intelligence and Brain Research: Neural Networks, Deep Learning and the Future of Cognition
Deep Learning Applications in Image Analysis (Studies in Big Data Book 129)
Generatives Deep Learning Maschinen das Malen, Schreiben und Komponieren beibringen
From Deep Learning to Rational Machines What the History of Philosophy Can Teach Us about the Future of Artificial Intelligence
From Deep Learning to Rational Machines: What the History of Philosophy Can Teach Us about the Future of Artificial Intelligence
From Deep Learning to Rational Machines What the History of Philosophy Can Teach Us about the Future of Artificial Intelligence