Open-source project that creates or edits images with generative AI and text-based controls.
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aipresentationmakers.com
A review site for AI presentation makers, presenting examples and in-depth reviews of more than 20 tools for work and school use, with recommendations for PowerPoint and creative presentations. It also covers Plus AI, an add-in for PowerPoint that creates new slide decks, edits existing presentations, or reformats slides using AI.
astroml.org
astroML is a Python module for machine learning and data mining built on numpy, scipy, scikit-learn, matplotlib and astropy, distributed under the 3-clause BSD license. It provides statistical and machine learning routines for analyzing astronomical data, loaders for open astronomical datasets, and examples of analyzing and visualizing datasets. The project was started in 2012 to accompany a textbook on statistics, data mining and machine learning in astronomy.
github.com
BayesO is a Python framework for Bayesian optimization, described as a simple but essential Bayesian optimization package. It is installed via pip and is tested on Python 3.8 through 3.12. The repository includes documentation, examples and tests, and is released under the MIT License.
github.com
Candle is a minimalist machine learning framework for Rust with a focus on performance, including GPU support, and ease of use. It provides examples and online browser demos for models such as whisper, LLaMA2, T5, yolo and Segment Anything.
cartography-of-generative-ai.net
Cartography of generative AI is a project presenting a mapped account of generative AI in multiple languages. It discusses how tools automate writing and image generation through examples and statistical models trained on datasets, and examines the extraction of internet content for training datasets and related controversies.
github.com
Official plugin resources and examples for extending Claude-based workflows.
matthewmcateer.me
A blog post explaining CLIP, a transformer model from OpenAI that matches text embeddings with image embeddings. It offers high-level prompt engineering tips for generative art and includes over 3500 prompt output examples, along with a section of Colab notebook links.
github.com
Data Driven Code is a GitHub repository containing code from a PyCon Canada 2016 session. The repository provides resources and examples related to data-driven programming techniques presented at the conference.
datascientistjourney.wordpress.com
A blog documenting a self-designed open source data science master's program. Posts cover a six-month plan to become a data scientist, study examples after one month, MOOCs versus classroom learning, and a final project using the D3.js library to present what was learned.
deepswe.datacurve.ai
DeepSWE is a benchmarking platform that evaluates frontier coding agents on original, long-horizon software engineering tasks. It provides a public leaderboard, task examples, and tracks results across 113 tasks, 91 repositories, 5 programming languages, and 28 models.
hub.docker.com
This Docker Hub listing provides the krohling/bondai Docker image for the BondAI agent tool. The 258.4 MB image was last updated almost 3 years ago. Users can run the image via a Docker command that mounts a local volume and configures an OpenAI API key, and can refer to the BondAI homepage for full documentation, examples, and API specifications.
github.com
Gadfly is a Julia package for creating statistical graphics. Developed by GiovineItalia, it provides a grammar of graphics for generating visualizations in Julia. The repository includes documentation, examples, and installation instructions, and is open source.
gpt3demo.com
800+ ChatGPT and GPT-3 Examples, Demos, Apps, Showcase, and Generative AI Use-cases.
gpt4demo.com
GPT-4 Examples, Demos, Apps, Showcase, and Generative AI Use-cases.
llm-book.com
Hands-On Large Language Models is an illustrated guide to large language models. It includes over 275 custom figures, working code examples, timelines, and references to key research papers. The book has received positive reviews from Andrew Ng, Nils Reimers, Josh Starmer, Luis Serrano, Leland McInnes, and Prof. DDr. Roman Egger.
github.com
Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
freecodecamp.org
A freeCodeCamp handbook for developers on organizing AI agents for real business cases. It covers prerequisites, large language models, definitions of AI agents, and a decision algorithm for creating optimal agents, including checking budget, starting with one agent, and measuring performance. It uses a Google Research, Google DeepMind, and MIT paper as its primary source and code examples in a Google Colab notebook.
htmlwidgets.org
HTML widgets are R packages that produce interactive web visualizations, working like R plots. A line or two of R code produces a D3 graphic or Leaflet map. Widgets run at the R console and can be embedded in R Markdown reports and Shiny web applications. The page lists widget examples including Leaflet, dygraphs, Plotly and Highcharter, and describes composing dashboards with flexdashboard and linking widgets with crosstalk. New widgets can be developed by bridging R and JavaScript.
imbalanced-learn.org
An open source, MIT-licensed Python library imported as imblearn that relies on scikit-learn. It provides tools for classification with imbalanced classes. The documentation includes installation guides, a user guide, an API reference and a gallery of examples.
github.com
The oneAPI Data Analytics Library (oneDAL) is a library for data analytics. It is hosted on GitHub under the uxlfoundation/oneDAL repository. The repository provides usage examples, installation instructions, and documentation.
github.com
ipychart is a Python library that brings the power of Chart.js to Python. It is hosted on GitHub at https://github.com/nicohlr/ipychart. The repository includes installation instructions, documentation, usage examples, and development information.
github.com
JSMLT is an open source JavaScript library for education in machine learning. It implements supervised learning algorithms, including SVM, random forest, decision tree, perceptron, neural networks, k-nearest neighbors and logistic regression, and provides visualization examples for exploring how the algorithms work.
colab.research.google.com
Notebook with examples of using Jupyter Widgets in Colab, allowing interactive inputs.