YelamanBaidol

YelamanBaidol's Stars

• ncss-tech/sda-lib

  Soil Data Access is the name of a suite of web services and applications whose purpose is to meet requirements for requesting and delivering soil survey spatial and tabular data that are not being met by the current Web Soil Survey and Geospatial Data Gateway websites.

  Language:HTML54

• usda-ars-ussl/rosetta-soil

  Implementation of the Rosetta pedotransfer function model for predicting unsaturated soil hydraulic parameters.

  Language:Python258

• ncss-tech/rosettaPTF

  R frontend for the Python rosetta-soil module. Uses {reticulate} to wrap the Rosetta pedotransfer functions and provide unsaturated soil hydraulic parameter estimates from basic soil properties.

  Language:R81

• ncss-tech/stats_for_soil_survey

  S4SS: Statistics for Soil Survey

  Language:HTML319

• ncss-tech/soilDB

  soilDB: Simplified Access to National Cooperative Soil Survey Databases

  Language:R8120

• catherinedevlin/ipython-sql

  %%sql magic for IPython, hopefully evolving into full SQL client

  Language:Python1.8k369

• automeris-io/WebPlotDigitizer

  Computer vision assisted tool to extract numerical data from plot images.

  Language:JavaScript2.6k360

• csev/py4e

  Web site for www.py4e.com and source to the Python 3.0 textbook

  Language:JavaScript2.9k1.8k

• libgenapps/LibgenDesktop

  Language:C#1.8k215

• EbookFoundation/free-programming-books

  :books: Freely available programming books

  334k61.2k

• microsoft/ML-For-Beginners

  12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

  Language:HTML69.1k14.3k

• cwang1291/Artificial-Intelligence

  This course covers fundamental artificial intelligence and machine learning techniques useful for developing intelligent software tools to support engineering design and other engineering activities. The computational techniques covered include: search, constraint satisfaction, probability, data mining, pattern recognition, neural networks, optimization, and evolutionary computation. The course will examine both the theory behind these techniques and the issues related to their efficient implementation. The application of the techniques to engineering tasks, such as design representation and automation will be explored.

  Language:Matlab52

• ulfaslak/artificial_neural_networks_and_deep_learning

  A 7 week introductory course to Deep Learning

  Language:Jupyter Notebook187

• Ashleshk/Machine-Learning-A-Z-hands-on-Python-And-R-in-data-Science

  Repository For Codes And Concept Taught in Udemy Course

  Language:Python6649

• nature-of-code/NOC-S17-2-Intelligence-Learning

  Syllabus for Part 2 of Nature of Code: "Intelligence and Learning" at ITP Spring 2017 Edit

  Language:JavaScript932342

• BloopAI/bloop

  bloop is a fast code search engine written in Rust.

  Language:Rust9.4k571

• xtekky/gpt4free

  The official gpt4free repository | various collection of powerful language models

  Language:Python60k13.2k

• highlight/highlight

  highlight.io: The open source, full-stack monitoring platform. Error monitoring, session replay, logging, distributed tracing, and more.

  Language:TypeScript7.5k350

• joaoventura/full-speed-python

  Full Speed Python: a book for self-learners

  Language:Makefile4.1k598