Search Results for "setting"

...Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting.

...Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal setting. 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.

...Implementations of several state-of-the-art algorithms are included for self-study and customization in your own applications. Please see the setup guide for more details on setting up your machine locally, on a data science virtual machine (DSVM) or on Azure Databricks. Independent or incubating algorithms and utilities are candidates for the contrib folder. 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.

...It includes functionality to load, process, and save datasets with support for different preprocessing & multicollinearity removal strategies with customizable parameter setting options.

Graphical user interface for gnuplot to create publication quality figure very quickly. It supports templates for fast formatting of graphics, different plot styles, insets, axis and label options. One important feature is storing metadata in png and pdf files that can be used to reload any graph saved with QuickPlot.

PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists. It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4...

CC2 is a customised, repackaged version of Cyclos 3.7 which is designed to * Allow small communities to get up and running quickly with the world’s leading alternative currency software * Improve the look and feel of Cyclos and make it more intuitive for users * Add additional reporting functionality (x and z reporting, automated invoicing) for business users **Please see the Release Note** on the Wiki Tab for background of this project and non-technical aspects of setting up Commnuity Currencies using CC2 If you have difficulties setting up the CC2 project, you may like to consider Cyclos4 communities - A free online version of Cyclos 4 which requires no technical knowledge or hosting to get up and running. Register here: https://communities.cyclos.org/register/app/form