BOOKS - PROGRAMMING - Session-Based Recommender Systems Using Deep Learning
Session-Based Recommender Systems Using Deep Learning - Reza Ravanmehr, Rezvan Mohamadrezaei 2024 PDF Springer BOOKS PROGRAMMING
ECO~15 kg CO²

1 TON

Views
8273

Telegram
 
Session-Based Recommender Systems Using Deep Learning
Author: Reza Ravanmehr, Rezvan Mohamadrezaei
Year: 2024
Pages: 314
Format: PDF
File size: 28.9 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
Deep Learning Illustrated A Visual, Interactive Guide to Artificial Intelligence
Introduction to Deep Learning for Engineers Using Python and Google Cloud Platform
Data-Driven Clinical Decision-Making Using Deep Learning in Imaging
Federated Deep Learning for Healthcare A Practical Guide with Challenges and Opportunities
Deep Learning in Medical Image Processing and Analysis (Healthcare Technologies)
Deep Learning Techniques and Optimization Strategies in Big Data Analytics
Deep Learning Examples with PyTorch and fastai A Developers| Cookbook
Geometry of Deep Learning: A Signal Processing Perspective (Mathematics in Industry, 37)
Deep Reinforcement Learning and Its Industrial Use Cases AI for Real-World Applications
Designing Machine Learning Systems
Control Systems and Reinforcement Learning
Machine Learning-Based Modelling in Atomic Layer Deposition Processes
Reinforcement Learning for Finance A Python-Based Introduction (Early Release)
Machine Learning for Kids A Project-Based Introduction to Artificial Intelligence
Machine Learning-based Design and Optimization of High-Speed Circuits
Learning And Living. A Five-Year Plan Based On The Cems. Rule Of Life.
Reinforcement Learning for Finance A Python-Based Introduction (Final Release)
The Learning-Centered Kindergarten: 10 Keys to Success for Standards-Based Classrooms
Reinforcement Learning for Finance A Python-Based Introduction (Final Release)
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
How Do We Learn?: A Scientific Approach to Learning and Teaching (Evidence-Based Education)
Reinforcement Learning for Finance A Python-Based Introduction (Early Release)
New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms
New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms
Deep Learning Theory, Architectures and Applications in Speech, Image and Language Processing
Statistical Process Monitoring using Advanced Data-Driven and Deep Learning Approaches
Foundations of Deep Reinforcement Learning Theory and Practice in Python (Rough Cuts)
Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics
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 at Scale At the Intersection of Hardware, Software, and Data (Third Early Release)
Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play
Deep Learning at Scale At the Intersection of Hardware, Software, and Data (Third Early Release)
Deep Learning for Agricultural Visual Perception: Crop Pest and Disease Detection
Deep Learning for Coders with fastai and PyTorch AI Applications Without a PhD (Early Release)
Deep Learning for Medical Image Analysis (The MICCAI Society book Series)
Deep Learning Theory, Architectures and Applications in Speech, Image and Language Processing
Real-World Natural Language Processing Practical applications with deep learning