PyBroker is a Python framework for developing algorithmic trading strategies with a focus on machine learning. It provides a backtesting engine built in NumPy and accelerated with Numba, model training and backtesting using Walkforward Analysis, parameter optimization with Optuna, and access to historical data from Alpaca, Yahoo Finance, and AKShare. It supports Python 3.11+ on Windows, Mac, and Linux.
Weka is open-source machine learning software issued under the GNU General Public License. It runs in Java and is presented as a workbench for data mining, with download, documentation, courses and FAQ resources and datasets available on the project site.
ML-Ops is a site about Machine Learning Operations. It covers motivation for MLOps, designing ML-powered software, the end-to-end ML workflow lifecycle, three levels of ML-based software, MLOps principles, CRISP-ML(Q), the MLOps Stack Canvas and ML model governance. It describes MLOps as aiming to unify the release cycle for machine learning and software.
Licensing is neither feasible nor effective for addressing AI risks provides machine-learning models, research, training resources, or evaluation…
A portfolio page for Greg (Grzegorz) Surma that lists side projects related to machine learning, computer vision, self-driving cars and iOS development. It indexes apps and experiments, including AI avatars, image filters, depth estimators, a CNN explainer and games, with the tools and platforms used for each.
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. It provides high-level APIs in Java, Scala, Python and R, and supports Spark SQL, pandas API on Spark, MLlib, GraphX and Structured Streaming. The documentation covers downloads, the shell and client applications.
Apache OpenNLP is a machine learning based toolkit for the processing of natural language text. It supports tasks such as sentence segmentation, tokenization, lemmatization, part-of-speech tagging, named entity extraction, chunking, parsing, language detection and coreference resolution. The project is developed by volunteers and welcomes contributions, from small documentation fixes to new components.
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Weka is open-source machine learning software issued under the GNU General Public License. It runs in Java and is presented as a workbench for data mining, with download, documentation, courses and FAQ resources and datasets available on the project site.
ML-Ops is a site about Machine Learning Operations. It covers motivation for MLOps, designing ML-powered software, the end-to-end ML workflow lifecycle, three levels of ML-based software, MLOps principles, CRISP-ML(Q), the MLOps Stack Canvas and ML model governance. It describes MLOps as aiming to unify the release cycle for machine learning and software.
Licensing is neither feasible nor effective for addressing AI risks provides machine-learning models, research, training resources, or evaluation…
A portfolio page for Greg (Grzegorz) Surma that lists side projects related to machine learning, computer vision, self-driving cars and iOS development. It indexes apps and experiments, including AI avatars, image filters, depth estimators, a CNN explainer and games, with the tools and platforms used for each.
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. It provides high-level APIs in Java, Scala, Python and R, and supports Spark SQL, pandas API on Spark, MLlib, GraphX and Structured Streaming. The documentation covers downloads, the shell and client applications.
Apache OpenNLP is a machine learning based toolkit for the processing of natural language text. It supports tasks such as sentence segmentation, tokenization, lemmatization, part-of-speech tagging, named entity extraction, chunking, parsing, language detection and coreference resolution. The project is developed by volunteers and welcomes contributions, from small documentation fixes to new components.
