Search Results for "spreadsheet machine learning"
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Showing 17 open source projects for "spreadsheet machine learning"
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JQM Java Quine McCluskey
JQM - Java Quine McCluskey for minimization of Boolean functions.
Java Quine McCluskey (JQM) implements the Quine-McCluskey algorithm with Petrick’s Method for minimizing Boolean functions. Designed for both education and industrial application, it handles up to 16 variables and functions. Uniquely, JQM bridges the gap between theory and practice: it visualizes the solution process with generated Karnaugh Maps for students, while supporting PLC engineers by exporting results to Structured Text (ST) and Ladder Diagram (LD). The software includes a GUI for... -
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The Art of Programming
A collection of practical tips can be found at the bottom of this page
...In July 2023, work on the second edition was announced, which expands the project with updated content, new problems inspired by recent big-tech interviews, and introductions to modern machine learning techniques such as XGBoost, CNNs, RNNs, and LSTMs. This collection serves both as a historical record of algorithm problem-solving and as a living resource for programmers preparing for interviews. -
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Ceka
Crowd Environment and its Knowledge Analysis
A knowledge analysis tool for crowdsourcing based on Weka. We also have a Python version of Crowdsourcing Learning: CrowdwiseKit on GitHub (https://github.com/tssai-lab/CrowdwiseKit). -
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MIT Deep Learning Book
MIT Deep Learning Book in PDF format by Ian Goodfellow
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville. -
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jMIR
Music research software
...It also includes tools for managing and profiling large music collections and for checking audio for production errors. jMIR includes software for extracting features, applying machine learning algorithms, applying heuristic error error checkers, mining metadata and analyzing metadata. -
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Open Cezeri Library
Effective Linear Algebra and Computer Vision Library with JAVA
...To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1- Vision: It can access web cams, imaging source industrial cameras for manuel settings and advanced issues. Studies on accesing Leapmotion and Kinect is still under-development. 2- Machine learning: It uses Weka Software tool and some personel coded ML algorithms 3- CMatrix: Special matrix library called as CMatrix meaning Cezeri Maztrix Class. ... -
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GUAJE FUZZY
Free software for generating understandable and accurate fuzzy systems
GUAJE stands for Generating Understandable and Accurate fuzzy models in a Java Environment. Thus, it is a free software tool (licensed under GPL-v3) with the aim of supporting the design of interpretable and accurate fuzzy systems by means of combining several preexisting open source tools, taking profit from the main advantages of all of them. It is a user-friendly portable tool designed and developed in order to make easier knowledge extraction and representation for fuzzy systems, paying... -
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SCORM (1.3) E-learning Development Tool
All you need to develop your e-learning courses!
This is a preconfigured VirtualBox Virtual Machine containing all you need to develop SCORM packages (1.3) for your e-learning courses. Using a Java Wizard, it is possible to add your content to a preconfigured e-learning course and export it in SCORM 1.3 format. Moodle 2.7 LMS is included to test your SCORM packages. The preconfigured e-learning course uses HTML5 tags to allow learners to enjoy the course using mobile devices (smartphones, tablets). -
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Myrtle
A simple programmable spreadsheet for learning statistics.
Myrtle is a simple programmable spreadsheet and statistical analysis software specifically designed for learning statistics. It provides the standard spreadsheet functionality one would expect like multiple tabbed sheets, relative and absolute row and column referencing in formulas, and a large catalog of built-in functions. Functions specific to logic and computer science, mathematics, probability, and statistics are available. -
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Java Based Artificial Intelligence - an experimental approach to machine self-learning The project is meant as an experiment: it's just fooling around with code and seeing what happens. Don't expect Skynet to come rolling out of it.
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Enable the user to talk to the calculator to enter the numbers and operations or write them using a drawing panel , it support both English and Arabic languages.It have text to speech of the entered numbers/operations and reading the results.
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Maui is a multi-purpose automatic topic indexing algorithm. Given a document, Maui automatically identifies its topics. Depending on the task topics are tags, keywords, keyphrases, vocabulary terms, descriptors or Wikipedia titles.
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Hipo is a hypothetical computer to facilitate the learning of machine language. The student can use hipo to develop simple programs and understand the internal logic of a computer. There is a plan to implement Donald Knuth's MMIX machine language, also.
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KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
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Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
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