Fit interpretable models. Explain blackbox machine learning.
- machine-learning
- interpretability
- gradient-boosting
- blackbox
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Fit interpretable models. Explain blackbox machine learning.
A mostly reasonable approach to CSS and Sass.
Dockerfile for Apache Kafka
🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.
A Python scikit for building and analyzing recommender systems
Apache OpenWhisk is an open source serverless cloud platform
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A utility for arming (creating) many bees (micro EC2 instances) to attack (load test) targets (web applications).
Fast persistent recoverable log and key-value store + cache, in C# and C++.
Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
Open-source offline translation library written in Python
A lightweight, object-oriented finite state machine implementation in Python with many extensions
Powerful system container and virtual machine manager
Instant Kubernetes-Native Application Observability
Statistical Machine Intelligence & Learning Engine
Apache Camel is an open source integration framework with 350+ connectors. Write routes in Java, YAML, or XML. Run on Spring Boot, Quarkus, or standalone. Apache License 2.0.
Upserts, Deletes And Incremental Processing on Big Data.
Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
Apache KIE (Knowledge Is Everything) is the home of Drools, OptaPlanner, jBPM, and Kogito.
A lightweight graphic library providing 2d draw for Apache ECharts
Apache NiFi
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
A simple library for creating state machines in C# code
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility