Introduction to Neural Networks
CS-449: Neural Networks Fall 99 Instructor: Genevieve Orr Willamette University Lecture Notes prepared by Genevieve Orr, Nici Schraudolph, and Fred Cummins Course content Summary Our goal is to introduce students to a powerful class of model, the Neural Network. In fact, this is a broad term which includes many diverse models and approaches. We will first motivate networks by analogy to the brain.
Neural Network Tutorial
Introduction I have been interested in artificial intelligence and artificial life for years and I read most of the popular books printed on the subject. I developed a grasp of most of the topics yet neural networks always seemed to elude me. Sure, I could explain their architecture but as to how they actually worked and how they were implemented… well that was a complete mystery to me, as much ma
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Neural network (machine learning) - Wikipedia
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the neuronal organization found in the biological neural networks in animal brains.[1][2] An ANN is made of connected units or nodes called artificial neurons, which loosely model the neurons in a brain. These are connected by edges, which model the synapses in a brain
ニューラルネットワークと正則化 - yukobaのブログ
フィードフォワードニューラルネットワークをはじめとして、各種モデルはパラメータ数が多いと、不適切な過学習をします。パラメータ数を減らすのがまず最初に検討すべき事ですが、正則化項をつけるという解決方法もあります。詳細は、PRML本（パターン認識と機械学習 上 - ベイズ理論による統計的予測）のp.142やp.258をご覧ください。 フィードフォワードニューラルネットワークの正則化項は隠れ層、出力層、両方につけられるのですが、隠れ層につけると入力軸方向の高周波成分を除去します。出力層につけると、出力軸方向の小さな振幅を除去します。 上手い例ができたので、以下に載せます。関数は、 です。sinの方がノイズで、希望としては、を見つけ出して欲しいとします。 まず、下記グラフ（画像）が隠れ層の人工ニューロンが8つの場合。綺麗に学習しています。これが正攻法。 次に、sinを認識させるために、人工ニューロ
Java Neural Network Framework Neuroph
Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use. Features Supports Multi Layer Perceptrons with BackpropagationImage Recognition SupportEasy to use GUI for creating and experimenting with NNSupports various other n
Encog Machine Learning Framework
Encog is a pure-Java/C# machine learning framework that I created back in 2008 to support genetic programming, NEAT/HyperNEAT, and other neural network technologies. Originally, Encog was created to support research for my master’s degree and early books. The neural network aspects of Encog proved popular, and Encog was used by a number of people and is cited by 952 academic papers in Google Schol
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GNU/Linux AI & Alife HOWTO: Connectionism
Amazon.com: Introduction To The Theory Of Neural Computation (Santa Fe Institute Series): Hertz, John A., Krogh, Anders S., Palmer, Richard G.: Books
EE373B HomePage
A Brief Introduction to Neural Networks
Neuro AI | Artificial Neural Networks, Algorithms, tutorials and sofware
http://page.mi.fu-berlin.de/rojas/neural/
Neuroph on Hadoop: Massive Parallel Neural Network System? - DZone Big Data
https://www.certpal.com/blogs/2010/04/java-neural-networks-and-neuroph-a-tutorial/
Neuroph: Smart Java Apps with Neural Networks (Part 1) - DZone
Basic Neural Network Tutorial : C++ Implementation and Source Code
Basic Neural Network Tutorial – Theory
an Object Oriented Neural Engine