zahidaramai Goto Github PK

2016-ml-contest

Machine learning contest - October 2016 TLE

2daycourse

2-Day Course – Spatial Modeling with Geostatistics

adventures-in-ml-code

This repository holds all the code for the site http://www.adventuresinmachinelearning.com

animate.css

🍿 A cross-browser library of CSS animations. As easy to use as an easy thing.

aspittel.github.io

Personal Site

avo-from-xlines-in-python

X lines of Python

avo_app

Geophysical analysis app for Android; AppInventor project

basic-well-log-interpretation

Basic Well Log Interpretation with python, pandas, matplotlib

billplz-for-givewp

Accept Payment using Billplz by using this plugin

bootstrapbayeserroranalysis

Any model prediction error analysis using bootstrap and bayesian approaches, then applying correction

br-net

calculateshopee

This is simple javascript to calculate your total lifetime spent/purchase and total number of order on Shopee.

catboost

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 computation on CPU and GPU.

cloud-annotations

🐝 Custom Object Detection and Classification Training

cloud-annotations-client

Source for the Cloud Annotations tool

commercejs-nextjs

Commerce demo store built for the Jamstack. Built with Commerce.js, Next.js, and can be one-click deployed to Netlify. Includes product catalog, categories, variants, cart, checkout, payments (Stripe) order confirmation, and printable receipts.

complex-cnn-seismic

data-science--cheat-sheet

Bunch of Data Science Cheat Sheets

deoldify

A Deep Learning based project for colorizing and restoring old images (and video!)

depthconversion

Seismic Depth Conversion using Quadratic Functions

digidisc

Digital discovery for geoscientists

econstants

Computation of elastic constants and anisotropy from logs

facies_classification_benchmark

The repository includes PyTorch code, and the data, to reproduce the results for our paper titled "A Machine Learning Benchmark for Facies Classification" (published in the SEG Interpretation Journal, August 2019).

faciesclassification-tensorflow

Machine Learning Algorithm using tensorflow to classify facies from well log data

faciesnet-with-f3-seismic-trained-model

Software for detection of given facies

faultseg

FaultSeg: using synthetic datasets to train an end-to-end convolutional neural network for 3D fault segmentation

fga-geoseg

Implementations of various neural network architectures to infer the interface depth of simulations of the elastic wave equation with the frozen gaussian approximation.

fortify-ui

Laravel Fortify driven replacement to the Laravel UI package

fuzzylas

Fuzzy search for well log curves and tools

geological-log-data-machine-learning-with-python

A geological log data from a well in Kansas, USA is analyzed using Machine Learning (M.L.) techniques in Python. The data is overviewed, cleaned and analyzed for important patterns and relationships with which we found relationships of logs with each other and correlation of types of formations with the logs. Using this, we can eliminate the use of logs which are correlated or have no relative importance to the type of formation when we have prior geological knowledge of the area. Also, predictions of formation type were made successfully once the data is trained with the M.L. algorithms.