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A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
A game theoretic approach to explain the output of any machine learning model.
FastAPI framework, high performance, easy to learn, fast to code, ready for production
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports comp…
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
STAT 154: Modern Statistical Prediction and Machine Learning
Data Mining en Economia y Finanzas 2024
This is a template repository with developer tooling already included so you can get up and running with confidence.
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
Practice questions for the Azure AI-900 exam that helped me pass first time.
Free monospaced font with programming ligatures
A project using deep learning to forecast stock prices and covariance. Uses multiple threads to gather data and optimize portfolio using numerous APIs.
Open source business application platform for fast development
assertions for kotlin inspired by assertj
Konsist is a powerful static code analyzer tailored for Kotlin, focused on ensuring codebase consistency and adherence to coding conventions.
Questions, Solutions & Labs of Microsoft's Official Power BI Certification.
Backup for NYC TLC data for the DE Zoomcamp course
This repository will contain all of the resources for the Mage component of the Data Engineering Zoomcamp: https://github.com/DataTalksClub/data-engineering-zoomcamp/tree/main
modelo CRISP-DM para analizar datos espaciales sobre la contaminación del aire