Projects with this topic
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Python API and CLI for remote submission and monitoring of Python applications on HPC.
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The Open Energy Tracker is an open data platform for monitoring and visualizing energy policy targets.
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official implementation for the manuscript 'AI-based association analysis for medical imaging using latent-space geometric confounder correction'
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Rumdpy implements molecular dynamics on GPU's in Python, relying heavily on the numba package (numba.org) which does JIT (Just-In-Time) compilation both to CPU and GPU (cuda)
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A two-channel deconvolution method with Starlet regularization. The code also features a PSF reconstruction algorithm.
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A Python library for Secure and Explainable Machine Learning
Documentation available @ https://secml.gitlab.io
Follow us on Twitter @ https://twitter.com/secml_py
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Pyxel is a general detector simulation framework (https://esa.gitlab.io/pyxel). An easy-to-use framework that can simulate a variety of imaging detector effects combined on images (e.g. radiation and optical effects, noises) made by CCD or CMOS-based detectors.
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programas para medición de variables agro-hidrológicas. Datos obtenidos de esas mediciones y su correspondiente análisis.
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The Real-Time Insights from Twitter project offers a comprehensive platform for monitoring and analyzing Twitter's dynamic conversations. By leveraging the Twitter API, this project facilitates the real-time collection, analysis, and visualization of tweets, providing valuable insights into public sentiment, trending topics, and other significant metrics.
Objectives:
Data Collection: The project uses the Tweepy library to stream tweets based on specific keywords, hashtags, or other criteria, capturing data that includes tweet content, user information, and metadata. Sentiment Analysis: By employing Natural Language Processing (NLP) tools like TextBlob, the project assesses the sentiment expressed in tweets, classifying them as positive, negative, or neutral. This helps in understanding public mood and opinion trends. Trend Identification: The project identifies and analyzes trending hashtags and topics, providing insights into what subjects are gaining traction or popularity over time. Visualization: Data analysis is further enhanced through visualizations using Matplotlib and Seaborn. These visual tools include time series plots, word clouds, and sentiment distribution charts, offering a clear view of trends and public discourse.
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Jupyter Notebooks illustrating Elementary Linear Algebra Concepts and Algorithms Youtube lectures
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“Schnittstelle zur Wahldatenbereitstellung”: An API and a UI to access data about elections concerning the Verfasste Studierendenschaft of the Universität Heidelberg. Contributions welcome!
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The impossible often has a kind of integrity to it which the merely improbable lacks.
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aGrUM is a C++ library designed for easily building applications using graphical models such as Bayesian networks, influence diagrams, decision trees, GAI networks or Markov decision processes.
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