Search Results for "scripts"
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Showing 29 open source projects for "scripts"
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Think Bayes
Code repository for Think Bayes
...Instead of heavy focus on continuous mathematics or calculus, the book emphasizes learning Bayesian inference by writing Python programs. The project includes code examples, scripts, and environments that correspond to the chapters of the book. Learners can run the code, experiment with probability distributions, compute posterior probabilities, and understand Bayesian updating via simulation and algorithmic methods. The book and code encourage thinking in terms of discrete approximations (sums over distributions) rather than continuous integrals, making it more accessible to many programmers. ... -
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LangChain Open Deep Research
Fully open source deep research agent
...The agent runs on LangGraph and can be explored locally through LangGraph Studio, an API, and generated API documentation. Environment settings control model choices, search services, MCP servers, and other research behavior. The repository also includes evaluation scripts for Deep Research Bench, enabling reproducible comparisons across difficult multilingual tasks. -
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Think Python 2
LaTeX source and supporting code for Think Python, 2nd edition
...The code includes all of the example programs, exercises, and supplementary files referenced in the book, allowing learners to run the examples, experiment, and extend them. The repository contains clean, well-commented Python scripts that are easy to follow and map directly to chapters of the text, covering topics like variables, control flow, functions, recursion, data structures (lists, dictionaries), classes and objects, file I/O, and algorithmic thinking. It also contains solutions or hints for many exercises so learners can check their work or explore alternative implementations. ... -
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xrayutilities
a package with useful scripts for X-ray diffraction physicists
xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). More... -
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QASystemOnMedicalKG
A tutorial and implement of disease centered Medical knowledge graph
...It collects structured information from vertical medical websites and imports the resulting entities and relationships into Neo4j. The included graph contains diseases, symptoms, drugs, foods, examinations, departments, and commercial drug products. Python scripts handle data collection, dictionary-based segmentation, graph construction, question classification, parsing, and database queries. The chatbot recognizes many question patterns, including symptoms, causes, complications, diet guidance, medications, examinations, prevention, treatment methods, and susceptible groups. Users configure Neo4j, build the database, and launch the graph-based chat program locally. ... -
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openSkyMatch
Matches OpenScience Observatories images with astronomical catalogs
openSkyMatch is a collection of Linux shell and Python scripts designed for the OpenScience Observatories program. It automates the identification and matching of detected celestial objects in locally captured FITS images with entries in large-scale sky catalogs, notably Pan-STARRS1 DR2 (II/389/ps1_dr2). The toolkit supports data preprocessing, coordinate correlation, and catalog-based validation of astronomical detections. -
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Summarize from Feedback
Code for "Learning to summarize from human feedback"
The summarize-from-feedback repository implements the methods from the paper “Learning to Summarize from Human Feedback”. Its purpose is to train a summarization model that better aligns with human preferences by first collecting human feedback (comparisons between summaries) to train a reward model, and then fine-tuning a policy (summarizer) to maximize that learned reward. The code includes different stages: a supervised baseline (i.e. standard summarization training), the reward modeling... -
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Reinforcement Learning Methods
Simple Reinforcement learning tutorials
...Each algorithm is structured with readable code, explanatory comments, and corresponding environment interaction loops so learners can easily trace how actions, rewards, and model updates connect. The project also includes demo scripts that visualize learning curves and allow students to observe policy improvement over training iterations. By using TensorFlow as the backbone, it highlights practical considerations such as tensor shapes, loss computation, optimization steps, and batching in an RL context. -
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python-tutorial
Practical Python tutorials, including Python basics
...It covers Python fundamentals, advanced language features, object-oriented programming, multithreading, databases, data science, Flask development, web crawling, and utility scripting. The project is intended for beginners learning Python and for working developers who want reference implementations for common scripts. Its examples are tested in a Python 3 environment and organized into topic-based directories. The repository also includes notebook-style learning materials for basic data types and core language concepts. It is useful as a structured self-study resource, classroom supplement, or quick reference for practical Python usage. -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference solutions so you can compare approaches and learn idiomatic patterns. The structure encourages incremental improvement—start with a brute-force idea, then refine to optimal time and space complexity. ... -
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pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
pytorch-tutorial is a highly popular educational repository that teaches deep learning with PyTorch through step-by-step examples and well-structured lessons. It is designed primarily for beginners and intermediate practitioners who want to understand PyTorch fundamentals and quickly move toward building real neural network models. The repository walks users through core concepts such as tensors, autograd, neural network modules, convolutional networks, recurrent networks, and transfer... -
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BPF Performance Tools
Official repository for the BPF Performance Tools book
BPF Performance Tools Book is the companion repository for Brendan Gregg’s book on Linux performance analysis using eBPF and BCC tracing technologies. The project contains scripts, examples, and reference material that demonstrate how to inspect kernel behavior, application performance, CPU usage, networking activity, file systems, and system bottlenecks in real time. It serves as both an educational resource and a practical toolkit for Linux engineers, SREs, and performance analysts working with modern observability workflows. ... -
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Evolution Strategies Starter
Code for the paper "Evolution Strategies.."
...This approach allows for efficient parallelization and robustness against worker termination, making it ideal for distributed execution on Amazon EC2 spot instances. The codebase supports building custom AMIs with Packer, integrates with MuJoCo for simulation-based experiments, and includes scripts for launching and managing large-scale runs. While no longer actively maintained, the repository serves as a historical and educational reference. -
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Learn Python the Hard Way
Concise study notes derived from “Learn Python the Hard Way”
This repository contains concise study notes derived from “Learn Python the Hard Way,” organized to reinforce core Python concepts through small, targeted examples. It emphasizes hands-on practice—short scripts, exercises, and explanations that help cement syntax, data structures, functions, and modules. The notes call out common gotchas, idioms, and style preferences so learners form good habits early. Because the content is intentionally compact, it’s easy to revisit a topic quickly when preparing for interviews or refreshing fundamentals. ... -
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Learning to Learn in TensorFlow
Learning to Learn in TensorFlow
Learning to Learn, created by Google DeepMind, is an experimental framework that implements meta-learning—training neural networks to learn optimization strategies themselves rather than relying on manually designed algorithms like Adam or SGD. The repository provides code for training and evaluating learned optimizers that can generalize across different problem types, such as quadratic functions and image classification tasks (MNIST and CIFAR-10). Using TensorFlow, it defines a... -
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Aurora Conky Theme
Aurora is a conky theme full of scripts
...Extra information and youtube explanation can be seen on youtube via these pages. http://erikdubois.be/linux/conky http://erikdubois.be/linux/install-conky-theme-aurora What can it do more than Conky normally can? - scripts for temperature, fans, names of hardware - hours of lifetime harddisks - spotify information and covers - gmail information - number of updates - rss via scripting - weather forecast - many different lua to make rings and such - netstat script - nvidia information - satelite image of world and europe - sensors script - sign and stars of today - transmission information -
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Matplotlib tutorial
Matplotlib tutorial for beginner
The Matplotlib tutorial repository is designed as a hands-on learning resource to help users — especially Python beginners — get started with Matplotlib for creating plots and charts. It provides a sequence of example scripts and notebooks that cover fundamental plotting tasks: line graphs, histograms, scatter plots, bar charts, customizing axes, labels, legends, and styling. This makes it ideal for someone learning data analysis or exploratory data visualization for the first time and needing concrete, runnable examples rather than abstract explanations. ... -
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SendMeSpamIDS is a python written honeypot. It includes HTTP, HTTPS, SMTP and many more, which are under constant development. The scripts support syslog and are ready for ELK integration.
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t2t-pipe
automatic alignment pipeline for parallel treebanks
The *Tree-to-Tree (t2t) Alignment Pipe* is a collection of python scripts, co-ordinating the process of automatic alignment of parallel treebanks from plain text files with a single call from a unix command line. Supported Languages: DE, FR, EN -
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Python scripts to extract, convert and import hardwar model data formats in Blender. Written for python 3.2 and Blender 2.57. To be run from blenders python console. Scripts are adaptable for related projects.
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The Python scripts for the conversion from the Chinese Pinyin transcription(ISO 7098) to International Phonetic Alphabet(IPA), comprised of a core module for developers and a flexible GUI application for the common end-users on Modern Chinese phonetics.
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...Developers can use JLink to add flowcharts to applications, serve a flow chart over the web in PDF or PNG, or dynamically create a flowchart with Javascript, Python or Ruby scripts
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A collection of python scripts for Chinesepod premium users: import CPod's vocab XML or CSV file to IFlash, download audio, fetch dialogue transcripts (and more to come). Includes an easy to use interface to the scripts for OSX-users.
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This project will provide translation of mathematical content, from TeX to MathML and vice-versa, and to graphics formats, as a web service. TeX, running as a daemon, is used for mathematical typography.
