Search Results for "classification"

ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The repository includes quizzes, solutions, and instructor materials to make the content usable in classrooms or self-study. ...

...This repository covers essential building blocks like sessions (for older TF versions), placeholders, variables, activation functions, and optimizers, before guiding learners through building end-to-end models for regression, classification, and data pipelines. Beyond the basics, the project includes examples of convolutional neural networks, recurrent networks, autoencoders, reinforcement learning, generative adversarial networks, and transfer learning workflows. By pairing code examples with conceptual explanations, the tutorials make abstract machine learning ideas accessible and encourage experimentation with TensorBoard visualization and distributed training.

MyCoRe is an Open Source project for the development of Repositories, Digital Library and archive solutions. The technical base of the system is formed of Java class libraries, XML technology and different database backends. Since 2015 we use https://mycore.atlassian.net/ for bug tracking. Please use our ticket system there.

...It provides a collection of notebooks that walk attendees from basic machine-learning concepts into practical modeling using the scikit-learn library. The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who already have a working Python environment and some familiarity with NumPy, SciPy, and Matplotlib. The repository specifies a clear list of dependencies so that participants can reproduce the environment used in the tutorial, and many downstream forks keep the content updated for newer versions of scikit-learn. ...

Deep-Learning-for-Medical-Applications is a repository that compiles deep learning methods, code implementations, and examples applied to medical imaging and healthcare data. The project addresses domain-specific challenges like segmentation, classification, detection, and multimodal data (e.g. MRI, CT, X-ray) using state-of-the-art architectures (e.g. U-Net, ResNet, GAN variants) tailored to medical constraints (small datasets, annotation costs, class imbalance). It includes Jupyter notebooks, model architectures, data preprocessing pipelines, and evaluation scripts specific to medical imaging tasks. ...

...cM uses crowdsourcing to leverage knowledge and computational resources of multiple users. For example, it includes multi-objective GCC, LLVM and ICC auto-tuning scenarios using shared benchmarks, codelets, data sets, tools, and combined with classification and predictive models. cM includes OpenME interactive interface to open up and expose internals of various third-party tools such as GCC, LLVM, run-time systems, etc. and connect them to cM through dynamic plugins that allows online analysis and tuning of programs and architectures. Live repo: http://c-mind.org/repo

ThManager is a tool for creating and visualizing knowledge organization models, such as thesauri, classification schemes, glosaries and other types of controlled vocabulary in SKOS format

Semtinel is an application framework for the semi-automatic creation, maintenance and analysis of hierarchical concept schemes (thesaurus, classification or ontology). Semtinel supports the development of new analysis methods and visualization techniques

Facilitates data mining/natural language processing experiments to be executed on weblogs, such as classification, clustering and rating. As part of these experiments, it is possible to apply Latent Semantic Analysis.

Naive-Bayes based classification services for Avalon/Keel framework IOC containers.

Pattern recognition software package. It includes several classification and clustering algorithms. It can read data from a set of images, an ASCII file or a JDBC connection. A small TCP data server with its corresponding JDBC driver is included.

Books Library Automation System.<br> key features: <ul type="circle"> <li>book catalogue</li> <li>book classification (Dewey Decimal Classification)</li> <li>work with readers accounts<br> </ul>