Search Results for "data fit"
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Showing 48 open source projects for "data fit"
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gopro-dashboard-overlay
Programs to process GoPro MP4 & Generic GPX/FIT files
gopro-dashboard-overlay is a multimedia processing toolkit that generates data-rich overlays on videos using telemetry data from GoPro cameras or external GPS sources. It processes video files alongside GPX or FIT data to render dashboards displaying metrics such as speed, distance, and location directly onto footage. The system supports a wide range of layouts, including maps, gauges, and charts, which can be customized through configuration files. -
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Prophet
Tool for producing high quality forecasts for time series data
...We’ve found it to perform better than any other approach in the majority of cases. We fit models in Stan so that you get forecasts in just a few seconds. Get a reasonable forecast on messy data with no manual effort. Prophet is robust to outliers, missing data, and dramatic changes in your time series. -
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imodelsX
Interpretable prompting and models for NLP
Interpretable prompting and models for NLP (using large language models). Generates a prompt that explains patterns in data (Official) Explain the difference between two distributions. Find a natural-language prompt using input-gradients. Fit a better linear model using an LLM to extract embeddings. Fit better decision trees using an LLM to expand features. Finetune a single linear layer on top of LLM embeddings. Use these just a like a sci-kit-learn model. -
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Dask
Parallel computing with task scheduling
...It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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Feature-engine
Feature engineering package with sklearn like functionality
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow Scikit-learn's functionality with fit() and transform() methods to learn the transforming parameters from the data and then transform it. -
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marimo
A reactive notebook for Python
marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots, make working with data feel refreshingly fast, futuristic, and intuitive. Version with git, run as Python scripts, import symbols from a notebook into other notebooks or Python files, and lint or format with your favorite tools. ... -
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Nano PDF Editor
Edit PDF files with Nano Banana
Nano PDF Editor is a minimalist, portable PDF viewer and toolkit that focuses on simplicity, speed, and ease of integration for applications that need basic PDF rendering without heavy dependencies. It provides core functionality such as page navigation, zooming, text selection, and rendering directly to native graphics surfaces, making it suitable for lightweight PDF viewing scenarios on desktop or embedded platforms. Designed to be easily embedded into larger software projects, Nano-PDF... -
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TensorFlow Probability
Probabilistic reasoning and statistical analysis in TensorFlow
...TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It's for data scientists, statisticians, ML researchers, and practitioners who want to encode domain knowledge to understand data and make predictions. Since TFP inherits the benefits of TensorFlow, you can build, fit, and deploy a model using a single language throughout the lifecycle of model exploration and production. TFP is open source and available on GitHub. ... -
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furl
The easiest way to parse and modify URLs in Python
...It also handles encoding automatically, including percent-encoding, Unicode domains, Unicode paths, and query strings. furl supports Python 3 and PyPy3 and is designed to be well tested and practical for everyday backend, scripting, and data-processing workflows. It is a good fit for developers who frequently need to clean, transform, generate, or normalize URLs in Python applications. -
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Recommenders
Best practices on recommendation systems
...This will house contributions which may not easily fit into the core repository or need time to refactor or mature the code and add necessary tests. -
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jlens
Companion code for the global workspace interpretability paper
...It transports residual-stream vectors from selected layers and positions into the final-layer basis using an averaged input-output Jacobian. The transformed vectors are decoded through the model’s own unembedding into ranked vocabulary predictions. The package can fit new lenses, load saved ones, apply them to prompts, and merge results from parallel fitting jobs. Interactive layer-by-position views reveal how token rankings evolve across the network and compare them with the model’s final output. It supports open-weight Hugging Face decoder models, with Qwen used in the included examples. The repository also provides synthetic evaluation data and an end-to-end notebook, but it is not maintained. -
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mlforecast
Scalable machine learning for time series forecasting
mlforecast is a time-series forecasting framework built around machine-learning models, designed to make forecasting both efficient and scalable. It lets you apply any regressor that follows the typical scikit-learn API, for example, gradient-boosted trees or linear models, to time-series data by automating much of the messy feature engineering and data preparation. Instead of writing custom code to build lagged features, rolling statistics, and date-based predictors, mlforecast generates... -
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PyMC3
Probabilistic programming in Python
PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. -
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models can be trained on potentially large datasets containing multiple time series, and some of the models offer a rich support for probabilistic forecasting. ... -
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rich
Rich is a Python library for rich text and beautiful formatting
...Effortlessly add rich output to your application, you can import the rich print method, which has the same signature as the builtin Python function. Rich can be installed in the Python REPL, so that any data structures will be pretty printed and highlighted. As you might expect, this will print "Hello World!" to the terminal. Note that unlike the builtin print function, Rich will word-wrap your text to fit within the terminal width. -
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PokeeResearch-7B
Pokee Deep Research Model Open Source Repo
...Because the system is modular, you can swap the search component, reader, or policy to fit private deployments or different data domains. It’s aimed at developers who want a transparent, hackable research agent they can run locally or wire into existing workflows. -
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gplearn
Genetic Programming in Python, with a scikit-learn inspired API
gplearn implements Genetic Programming in Python, with a scikit-learn-inspired and compatible API. While Genetic Programming (GP) can be used to perform a very wide variety of tasks, gplearn is purposefully constrained to solving symbolic regression problems. This is motivated by the scikit-learn ethos, of having powerful estimators that are straightforward to implement. Symbolic regression is a machine learning technique that aims to identify an underlying mathematical expression that best... -
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StatsForecast
Fast forecasting with statistical and econometric models
StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery... -
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KherveFitting
Fit X-ray Photoelectron Spectroscopy (XPS) and XAS data
⚠️ KherveFitting has moved. New releases will no longer be published here. Download the latest version from https://khervetools.com or directly from GitHub: https://github.com/KherveFitting/KherveFitting/releases/latest. This SourceForge page is kept for archival/older versions only. YouTube Channel: https://www.youtube.com/@xpsexamples-imperialcolleg6571 -
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FreeSEM
Free and open-source desktop application designed for SEM
...It allows users to visually build models using a drag-and-drop interface to create path diagrams and analyze relationships between observed and latent variables. The software supports methods such as exploratory factor analysis, covariance-based SEM, partial least squares SEM, and meta-SEM, and it provides model fit statistics like CFI, TLI, RMSEA, SRMR, and chi-square to evaluate models. It also enables exporting analysis results and reports to formats like Word, Excel, CSV, and PDF, making it useful for academic research and data analysis workflows. -
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GenX
X-Ray and Neutron Reflectivity Modeling
GenX is a scientific program to refine x-ray refelcetivity, neutron reflectivity and surface x-ray diffraction data using the differential evolution algorithm. GenX is very modular and highly extensible and can be used as a general fitting program. -
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BioXTAS RAW
Processing and analysis of Small Angle X-ray Scattering (SAXS) data.
BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis... -
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Micro Recorder (Mouse Auto Clicker)
Mouse and Keyboard action Record (Auto Click ) With Micro Recorder
Micro Recorder is an innovative software that allows users to capture their mouse and keyboard actions and replay them with precision. Whether you're looking to automate repetitive tasks, perform complex sequences, or simply save time, this tool makes it easy to record and replay desktop actions on-demand. With an intuitive interface and robust features, Micro Recorder is perfect for both beginners and professionals who need a reliable automation solution for their daily workflow. Enhance... -
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GromacsProSuite
Graphical User Interface for Gromacs
This tool is an integrated graphical interface that simplifies molecular dynamics simulations using Gromacs. It provides a structured, tab-based environment to set up, execute, and analyze simulations data without complex command-line operations. The software automates tasks such as topology generation, solvation, ion addition, minimization, equilibration, and production runs while executing GROMACS commands in the background. Built-in monitoring tracks CPU, RAM, and disk usage to ensure... -
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Tempico software
Software to control and analyze Tausand Tempico timing data
Tempico Software is designed to control the Tausand Tempico TP1004 and TP1204 devices, a time-to-digital converter that captures temporal differences from a common start signal across multiple channels. The software generates histograms from captured data, supports lifetime measurements via single-photon correlation (SPC), and displays real-time graphs with adjustable fitting options. It includes a 'Counts Estimation' panel to estimate count rates per channel over time, and a 'Time Stamping'...
