NeurApp Crack + PC/Windows [2022-Latest] NeurApp (Neural Approximate) is a user-friendly GUI based on IGLib, which can help you explore approximation by artificial neural networks (ANNs). It supports both 1D and 2D artificial neural network models, giving you the possibility to specify parameters and plot results. Explore approximation by ANNs It's not necessary to setup this tool since you can unzip the downloaded archive and double-click the.exe to reach the main app window. However, it cannot work unless you have.NET Framework or Mono installed on your computer. The interface is based on a large window with two tabs for separately configuring settings when it comes to 1D and 2D approximation. For 1D mode, you can enable a function defined by the user and set the number of training samples, along with bounds. Set properties for 1D and 2D approximation models For 2D approximation mode, it's possible to specify the training points on the X and Y axis, as well as to customize visualization settings related to the training points, original, approximation and contour graphs. In both cases, you can also set application error values (maximum and RMS training and verification), enter the number of neurons in hidden layers, set the max epochs and epochs in bundle, enter the RMS, learning rate and momentum, as well as indicate the input and output safety factor. The network can be trained with one click when everything is ready in NeurApp. Also, you can reset everything to default to restart from scratch. Unfortunately, there are no options implemented for copying the graph or data to the clipboard, exporting them to files, or printing them. Easy-to-use artificial neural network explorer The tool worked smoothly on Windows 10 in our tests. It had minimal impact on the computer's performance and generated neural network models quickly. All aspects considered, NeurApp offers a simple solution for producing ANN models based on 1D and 2D approximation settings. NeurApp Features: - Generate new artificial neural network models based on 1D and 2D approximation settings - Generate ANN models in.NET Framework 4.0, 4.5, and.NET Core - Generate ANN models based on Artificial Neural Network module - Generate ANN models in Python (neurapp.py) - Generate ANN models in PHP (neurapp.php) - Generate ANN models in C# (.NET) - Generate ANN models NeurApp Free Download * Generate and visualize 2D and 1D artificial neural networks * Set up all training parameters * Set up maximum and error values for the trained network * Export and apply the network to unknown data * 1D approximation mode * Training points: Number of training samples * Bounds: Min and Max values for training data * Error values: Maximum and RMS errors for training and verification data * Contour plots: Visualize the original and the approximated data in a contour plot * Approximation mode: Maximum number of hidden layers * Output safety factor: Regularization for output values * Learning rate: Setting of the learning rate * Momentum: Setting of the momentum * X Axis Label: Visible labels for the X axis * Y Axis Label: Visible labels for the Y axis * Max epochs and epochs in bundle: Maximum number of training epochs * RMS training error: RMS value for the training error * RMS verification error: RMS value for the verification error * Maximum error: Maximum error for verification * Maximum and RMS error: Maximum and RMS errors for the training and verification * Training sample: Training sample for the training mode * Training data: Training data for the training mode * Training points: Training points for the training mode * Verify sample: Verify sample for the training mode * 2D approximation mode * Training points: X and Y training points for the X and Y axes * Bounds: Min and Max values for training data * Error values: Maximum and RMS errors for training and verification data * Contour plots: Visualize the original and the approximated data in a contour plot * Maximum number of hidden layers: Maximum number of hidden layers for the ANN * Approximation mode: Maximum number of hidden layers * Output safety factor: Regularization for output values * Learning rate: Setting of the learning rate * Momentum: Setting of the momentum * X Axis Label: Visible labels for the X axis * Y Axis Label: Visible labels for the Y axis * Maximum epochs and epochs in bundle: Maximum number of training epochs * RMS training error: RMS value for the training error * RMS verification error: RMS value for the verification error * Maximum error: Maximum error for verification * Maximum and RMS error: Maximum and RMS errors for the training and verification * Training sample: Training sample for the training mode * Training data: Training data for the training mode * Training points: Training points for the training mode * Verify sample: Verify sample for the training mode * Tutorial and Help * Implemented project help: How to use NeurApp * Testing project: How to test a new network * Testing project: How to test an 8e68912320 NeurApp Crack+ - RMS: Root Mean Square - Epoch: Number of training epochs - Max Error: Maximum allowed training error - Min Error: Minimum allowed training error - Learning Rate: Learning rate. By default, it is set to 0.01 - Momentum: Momentum, for example, set to 0.5 - Safety Factor: Output safety factor. By default, it is set to 1.0 - Time: Time in seconds to compute - Training Data: Training data size in samples - Learning Rate and Momentum combination: Learning rate and momentum combination, for example, 0.01 and 0.5 - Learning Rate and Momentum: Learning rate and momentum - Time and Learning Rate: Time and learning rate - Time and Momentum: Time and momentum - Time and Learning Rate and Momentum: Time, learning rate and momentum License: The license is the same for the educational version of the tool as for the commercial one. GedcomXplorer (Xplorer) is a GTK/Qt GUI based on IGLib, which can help you explore and manage genealogical data stored in.ged format. It supports Gedcom format in addition to.ged files, which can be automatically recognized by searching. GedcomXplorer (Xplorer) It's not necessary to setup this tool since you can unzip the downloaded archive and double-click the.exe to reach the main app window. However, it cannot work unless you have GTK+ or Qt installed on your computer. The interface is based on a large window with four tabs for data management: File, Genes, Mapping and Genes/Mapping. GedcomXplorer (Xplorer) In the File tab, you can select the directory where your.ged files will be located, as well as specify the field where genealogical data are stored (first name, last name, sex, location and relationship). Access data and edit it You can access to data by clicking on the icons next to data fields. You can edit it by clicking on the icons next to data fields or using keyboard shortcuts. You can add a field to the tree view by clicking on the icon next to the data field. You can also make it hide in the tree view by selecting it. It is possible to link one or more records to a family group by specifying the ID, What's New in the? System Requirements: PC-Linux: AMD/Intel/Nvidia/ATI: CPU: Intel Pentium 4 or higher Memory: 1024MB RAM 2GB HDD/1GB RAM Graphics: 256MB or higher (unless you use a motherboard like ASUS P5K-E or Gigabyte GA-P35-DS4-B) NVIDIA 8800 GTX+ ATI Radeon 7800 GTX DirectX: 9.0c
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