Artificial Neural Network Ppt


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WEKA Classification Algorithms  v.1.8

A collection of plug-in algorithms for the WEKA machine learning workbench including artificial neural network (ANN) algorithms, and artificial immune system (AIS) algorithms.

Neural Creator  v.1.0

Neural Creator is our visually based neural network development system that can be trained to perform pattern matching, feature recognition or make predictions on noisy or fuzzy data. It has an easy to use interface and comes with example projects and ...





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NeuroXL Predictor  v.4.0.5

NeuroXL Predictor is a neural network forecasting tool that quickly and accurately solves forecasting,classification and estimation problems in Microsoft Excel. It is designed from the ground-up to aid experts in solving real-world forecasting problems.

EasyNN-plus

EasyNN-plus is a neural network system for Microsoft Windows. It makes the creation of neural networks easy. It allows the user to produce multilayer neural networks from a grid or from text files and images. The user can produce training, validating ...

SwingNN

Your data is imported into a grid and used to train a neural network. The input values are forced to swing beyond their limits. The output values are forecasted by the neural network. A new neural network is created using the new inputs and forecasted ...

JustNN

JustNN is a neural network system for Microsoft Windows. It makes the creation of neural networks easy. It allows the user to produce multilayer neural networks from a grid or from text files and images. The user can produce training, validating and querying ...

NeuroXL Classifier

NeuroXL Classifier is a neural network data classifying add-in for Microsoft Excel. ClassifierXL is designed for classifying data in Microsoft Excel. Its ability to handle numerous, often-interrelated variables makes it an excellent "data mining" tool ...

Digital Physiognomy  v.1 52

Digital Physiognomy uses a sophisticated neural network to identify correlations between facial features and psychological characteristics using photo identification techniques recognized by law enforcement professionals.
Only facial features that ...

NeuNet Pro  v.2.30.0014

NeuNet Pro is a complete neural network development system. Neural networks can be used for pattern recognition, data mining, market forecasting, medical diagnosis, sports handicapping... almost any activity where you need to make a prediction based on ...

Neuroph  v.2.5.1 RC 2

Neuroph is Java framework for neural network development. It contains well designed, open source Java library with small number of basic classes which correspond to basic NN concepts. Also has nice GUI neural network editor to quickly create Java neural ...

PredictorCMD  v.1.0

PredictorCMD is a neural network forecasting tool for the command line, can quickly and accurately solves forecasting and estimation problems and works from command line. It is designed from the ground-up to aid professionals in solving real-world forecasting ...

Neural Networks  v.4.3.7

Create neural networks fast and easy. Inspired by neurons and their connections in the brain, neural network is a representation used in machine learning. After running the back-propagation learning algorithm on a given set of examples, the neural network ...

Neural Pattern Recognition  v.6.0

Neural Pattern Recognition is implemented using Kohonen neural network and can recognize common stock patterns such as Head & Shoulders, Double Tops, Double Bottoms, Rounding Top, Rounding Bottom, Up Trend, Down Trend, Range, Triangle.
You could simply ...

NeuralCode Neural Networks Trading  v.1.0

NeuralCode is an industrial grade Artificial Neural Networks implementation for financial prediction. The software can take data like the Opening price, High, Low, Volume and other technical indicators for predicting or uncovering trends and patterns.

Java Neural Modeling Framework new GUI  v.1.0

Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.

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