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datahoarder-website-to-markdown is an open source project with code, documentation, and setup resources for web archiving and scraping.
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Spider Suite is an open source web scraping or crawling project for collecting website data.
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A public GitHub template repository for data science lifecycle projects. It provides a default directory structure including folders for code, data, docs, environments, notebooks, pipelines and tests, plus issue templates and a .github labels file. The source describes it as a launch-off point with minimal opinions. One manual step is creating labels from the labels file.
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Deepchecks is an open-source project for validating machine learning models and data from research to production. It includes built-in and custom checks and suites for tabular, NLP and CV validation, CI and testing management, and monitoring of deployed models. Installation is via pip.
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Analyzes structured data and helps produce queries, insights or visualizations.
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Statsmodels is a Python package that complements scipy for statistical computations, including descriptive statistics and estimation and inference for statistical models. It provides linear regression models, generalized linear models, discrete models, time series analysis, survival analysis, multivariate methods and a range of statistical tests.
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Evidently is an open-source observability framework for machine learning and large language models, hosted on GitHub under the evidentlyai organization. It enables users to evaluate, test, and monitor AI-powered systems and data pipelines, with support for use cases ranging from tabular data processing to generative AI, and includes more than 100 built-in metrics.
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GSmartControl is a graphical user interface for smartctl from the smartmontools package. It queries and controls SMART data on hard disk and solid-state drives, allowing users to inspect drive health and run tests. It supports SATA, PATA, and NVMe drives and runs on Linux, Windows, macOS, FreeBSD, and other BSD-style systems.
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Mamba-Chat is a chat language model built on a state-space model architecture rather than a transformer. The repository provides training and fine-tuning code based on a modified Huggingface Trainer class. The model is based on Mamba-2.8B and was fine-tuned on 16,000 samples of the HuggingFaceH4/ultrachat_200k dataset. Code is provided for testing and fine-tuning, including a command-line chatbot and a Gradio app.
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mcp-gsc helps monitor indexing, search performance, crawl data, and site visibility.
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A C++ implementation of an Ordinary Least Squares solver and linear regression engine with zero external dependencies. It uses a custom matrix library, modified Gram-Schmidt orthogonalization and QR decomposition. It includes a CSV test dataset from the Czech film market and computes error metrics such as RSS and MAE.
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PyTorch Geometric Temporal is a temporal extension library for PyTorch Geometric. It contains dynamic and temporal geometric deep learning, embedding and spatio-temporal regression methods from published research papers. It includes a dataset loader, train-test splitter and temporal snapshot iterator for dynamic and temporal graphs, with GPU support and benchmark datasets.
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Rapaio is a statistics, data mining, and machine learning toolbox written in Java. It includes distributions, hypothesis testing, Naive Bayes, logistic regression, decision trees, random forests, boosting, SVM, PCA, and KMeans.
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torchvision is a package of popular datasets, model architectures and common image transformations for computer vision. The repository holds documentation, benchmarks, examples, packaging, references and tests alongside the torchvision code. Installation instructions point to official guidance for stable torch and torchvision versions; building from source is covered on the contributing page.
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TurboBench is a data compression benchmark that includes more than 100 codecs and performs in-memory testing to avoid disk I/O effects. It supports multiple files, recursive directories and concatenation of small files into multiblock tests, and automatically creates a nightly GitHub release and benchmarks when submodules change.