Search Results for "text mining concept"
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Showing 12 open source projects for "text mining concept"
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Key-book
Proofs, cases, concept supplements, and reference explanations
The book "Introduction to Machine Learning Theory" (hereinafter referred to as "Introduction") written by Zhou Zhihua, Wang Wei, Gao Wei, and other teachers fills the regret of the lack of introductory works on machine learning theory in China. This book attempts to provide an introductory guide for readers interested in learning machine learning theory and researching machine learning theory in an easy-to-understand language. "Guide" mainly covers seven parts, corresponding to seven... -
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MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
...The project provides practical demonstrations of machine learning algorithms, data analysis workflows, and visualization techniques. Each notebook typically focuses on explaining a specific concept through step-by-step examples that combine explanatory text, code, and visual outputs. The repository covers a wide variety of data science topics such as predictive modeling, data preprocessing, statistical analysis, and feature engineering. Because the notebooks are designed as educational materials, they often emphasize readability and reproducibility so that readers can easily run and modify the examples. ... -
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Pattern
Web mining module for Python, with tools for scraping
...In addition to data mining features, the library offers natural language processing functionality including part-of-speech tagging, sentiment analysis, and n-gram extraction. The framework also includes machine learning algorithms that support classification, clustering, and vector space modeling for text analysis tasks. Another component of the library provides tools for analyzing and visualizing networks, making it useful for studying relationships between entities in large datasets. -
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FARM
Fast & easy transfer learning for NLP
...It's built upon transformers and provides additional features to simplify the life of developers: Parallelized preprocessing, highly modular design, multi-task learning, experiment tracking, easy debugging and close integration with AWS SageMaker. With FARM you can build fast proofs-of-concept for tasks like text classification, NER or question answering and transfer them easily into production. Easy fine-tuning of language models to your task and domain language. AMP optimizers (~35% faster) and parallel preprocessing (16 CPU cores => ~16x faster). Modular design of language models and prediction heads. Switch between heads or combine them for multitask learning. ... -
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VecText
Converting text to a structured representation
VecText is an application that converts raw text to a structured format suitable for various data mining software. The application is written in interpreted programming language Perl. A part of the functionality is realized by external modules (e.g., Lingua::Stem::Snowball for stemming). The graphical user interface enables user-friendly software employment without requiring specialized technical skills and knowledge of a particular programming language, names of libraries and their functions, etc. ... -
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TEXT2DATA
Text Analytics Platform
Bring Text Analytics Platform that uses NLP (Natural Language Processing) and Machine Learning to your work environment. Extract essential information from your text documents and let Artificial Intelligence save your time. Get detailed and agile reports on your unstructured data. -
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Python Data Science Tutorials
Common data analysis and machine learning tasks using python
...Its machine learning sections cover practical algorithms and libraries, including regression, classification, clustering, support vector machines, and computer vision resources. Additional material addresses text mining, sentiment analysis, serialization with pickle, AutoML, regular expressions, and web scraping. The repository is organized by topic so learners can use it as a study roadmap or troubleshooting index. Many links document the earlier Python data science ecosystem, making the project especially valuable as a broad historical resource collection. -
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GNAT
GNAT recognizes gene names in text and maps them to NCBI Entrez Gene
GNAT is a BioNLP/text mining tool to recognize and identify gene/protein names in natural language text. It will detect mentions of genes in text, such as PubMed/Medline abstracts, and disambiguate them to remove false positives and map them to the correct entry in the NCBI Entrez Gene database by gene ID. March 2017: We started to upload GNAT output on Medline. -
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sgmweka
Weka wrapper for the SGM toolkit for text classification and modeling.
Weka wrapper for the SGM toolkit for text classification and modeling. Provides Sparse Generative Models for scalable and accurate text classification and modeling for use in high-speed and large-scale text mining. Has lower time complexity of classification than comparable software due to inference based on sparse model representation and use of an inverted index. The provided .zip file is in the Weka package format, giving access to text classification. ... -
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Moara is a biological text mining tool and consists of a Java library and some auxiliary MySQL databases for gene/protein training and extraction of mentions and its further normalization and disambiguation.
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pySPACE
Signal Processing and Classification Environment in Python using YAML
...Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface. ...
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