BOOKS - PROGRAMMING - A Brief Introduction to Neural Networks
A Brief Introduction to Neural Networks - David Kriesel 2012 PDF Autoedici?n BOOKS PROGRAMMING
ECO~14 kg CO²

1 TON

Views
2305

Telegram
 
A Brief Introduction to Neural Networks
Author: David Kriesel
Year: 2012
Pages: 244
Format: PDF
File size: 5,6 MB.
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Machine Learning The Ultimate Beginners Guide For Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple
The Python Bible 7 in 1 Volumes One To Seven (Beginner, Intermediate, Data Science, Machine Learning, Finance, Neural Networks, Computer Vision)
Make Your Own Neural Network: An In-depth Visual Introduction For Beginners
New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms (Studies in Computational Intelligence, 1146)
Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics (Studies in Computational Intelligence Book 1096)
Artificial Intelligence An Illustrated History From Medieval Robots to Neural Networks (Sterling Illustrated Histories)
Power Converters and AC Electrical Drives with Linear Neural Networks (Energy, Power Electronics, and Machines)
Build Your Own Neural Networks Step-By-Step Explanation For Beginners
Quantum Machine Learning Quantum Algorithms and Neural Networks
Quantum Machine Learning Quantum Algorithms and Neural Networks
Neural Networks and Animal Behavior (Monographs in Behavior and Ecology, 29)
Hands-On Convolutional Neural Networks with TensorFlow: Solve computer vision problems with modeling in TensorFlow and Python
Artificial Intelligence: An Illustrated History: From Medieval Robots to Neural Networks (Union Square and Co. Illustrated Histories)
Learning Deep Learning Theory and Practice of Neural Networks, Computer Vision, NLP, and Transformers using TensorFlow
Python Deep Learning: Understand how deep neural networks work and apply them to real-world tasks
Beginning Mathematica and Wolfram for Data Science: Applications in Data Analysis, Machine Learning, and Neural Networks
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems
Learning Deep Learning Theory and Practice of Neural Networks, Computer Vision, NLP, and Transformers using TensorFlow (Rough Cuts)
Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets (Advances in Computer Vision and Pattern Recognition)
Wireless Sensor Networks An Introduction
Quantum Networks Introduction and Applications
Introduction to Wireless Sensor Networks
Introduction to Networks v6 Companion Guide
Connections: An Introduction to the Economics of Networks
Artificial Intelligence What You Need to Know About Machine Learning, Robotics, Deep Learning, Recommender Systems, Internet of Things, Neural Networks, Reinforcement Learning, and Our Future
5G An Introduction to the 5th Generation Mobile Networks
Introduction to Networks Companion Guide (CCNAv7)
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)
Machine Learning for Beginners A Math Guide to Mastering Deep Learning and Business Application. Understand How Artificial Intelligence, Data Science, and Neural Networks Work Through Real Examples
Building Electrical Systems and Distribution Networks An Introduction
An Introduction to 5G Wireless Networks Technology, Concepts and Use-cases
An Introduction to 5G Wireless Networks: Technology, Concepts and Use-cases
Communication Networks A Concise Introduction, 2nd Edition
Machine Learning for Beginners An Introductory Guide to Learn and Understand Artificial Intelligence, Neural Networks and Machine Learning
Learning PyTorch 2.0, Second Edition Utilize PyTorch 2.3 and CUDA 12 to experiment neural networks and Deep Learning models
Learning PyTorch 2.0, Second Edition Utilize PyTorch 2.3 and CUDA 12 to experiment neural networks and Deep Learning models
The Mathematics of Finite Networks An Introduction to Operator Graph Theory
Deep Learning and AI Superhero Mastering TensorFlow, Keras, and PyTorch Advanced Machine Learning and AI, Neural Networks, and Real-World Projects (Mastering the AI Revolution)
Practical Mathematics for AI and Deep Learning: A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning (English Edition)
Python Programming, Deep Learning 3 Books in 1 A Complete Guide for Beginners, Python Coding for AI, Neural Networks, & Machine Learning, Data Science/Analysis with Practical Exercises for Learners