boyoforex Goto Github PK
Name: Adebayo Ojo
Type: User
Company: Western University
Bio: I'm a geoscientist interested in solving impactful problems
Twitter: boyoforex
Location: London, Canada
Blog: aoojo.weebly.com
Name: Adebayo Ojo
Type: User
Company: Western University
Bio: I'm a geoscientist interested in solving impactful problems
Twitter: boyoforex
Location: London, Canada
Blog: aoojo.weebly.com
Machine learning contest - October 2016 TLE
Short course on geophysical inversion at RWTH Aachen University.
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.
Academic Website of Adebayo Oluwaseun Ojo
Python functions to preprocess and correlate ambient-noise data and extract phase-velocity curves
Codes for ambient noise tomography of Alaska
Collection of scripts to reproduce the results of Astic et al. (2020): forward modelling and joint inversion of potential fields data with petrophysical information (Petrophysically and geologically guided inversion: PGI)
A curated list of Earth Science's Artificial Intelligence (AI) tutorials, notebooks, software, datasets, courses, books, video lectures and papers. Contributions most welcome.
This repo provides an interactive GUI for BALTO within a Jupyter notebook. It uses ipywidgets (for the GUI), ipyleaflet (for interactive maps), pydap (for OpenDAP support), matplotlib and cartopy.
BayGrav3D is a Bayesian linear gravity inverse modeling program that inverts gravity data to determine the best-fitting densities of spatially discretized 3D subsurface prisms in a least-squares sense. We use a Bayesian approach to incorporate both data uncertainty and prior geophysical constraints, such as seismic data. Gaussian priors are applied to the model parameters as absolute equality constraints. BayGrav3D utilizes Tikhonov regularization as a relative equality constraint that smooths and stabilizes the inversion solution. Given gravity data and a set of priors, the inversion produces a solution to the model parameters (i.e. density) and the full covariance and resolution matrices to quantify the error on the solution. BayGrav3D is capable of working on both local and regional scales and with both simple and complex subsurface geometries. BayGrav3D is written is Matlab, and the release contains an example project with data with which users may test the scripts. A python release is planned sometime in the coming year or so. For more information on the methods, please refer to our paper - Hightower et al. (2020), A Bayesian 3-D linear gravity inversion for complex density distributions: application to the Puysegur subduction system, GJI, v. 223, p. 1899-1918. For using the program, please refer to the documentation (soon to be available on ReadTheDocs) and the commentary within the scripts.
McMC transdimensional Bayesian inversion of surface wave dispersion and receiver functions
A Python Package for seismic ambient noise cross-correlation and the frequency-Bessel transform method
Python codes for one-dimensional deep learning inversion of geophysical data
Dissertation project: "Estimating the accuracy of Moho depth estimates from gravity inversion"
a collection of jupyter notebooks that use SimPEG.EM
EvalML is an AutoML library written in python.
Using Machine learning to predict future Forex Prices
Predict direction of forex movement using word2vec and machine learning algorithms.
Foreign Exchange Trend Classification Via Machine Learning Methods
Using machine learning to predict hourly EUR/USD strategy. Based on the research paper: FOREX Trend Classification using Machine Learning Techniques
FOREX Trend Classification using Machine Learning Techniques.
Forex strategy based on https://www.researchgate.net/publication/236896558_FOREX_Daily_Trend_Prediction_using_Machine_Learning_Techniques?enrichId=rgreq-93372d8d52382de719821a1c4c52914b-XXX&enrichSource=Y292ZXJQYWdlOzIzNjg5NjU1ODtBUzoxMDEyNTk1NjY2NDkzNThAMTQwMTE1MzU3MDc1Nw%3D%3D&el=1_x_2&_esc=publicationCoverPdf
Directory of Fortran codes on GitHub, arranged by topic
Python package for Multi-Objective Bayesian Optimisation and Joint Inversion
non linear and linear geophysical inversions
open-geoscience
Collection of GMT (Generic Mapping Tools) scripts, jupyter notebooks (using PyGMT) and files (including digitized map content, colormaps, grid files etc.)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.