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abhishekdbihani.github.io

Use this template if you need a quick developer / data science portfolio! Based on a Minimal Jekyll theme for GitHub Pages.

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

aws-machine-learning-university-accelerated-cv

Machine Learning University: Accelerated Computer Vision Class

compaction_liggghts

This repository contains the workflow for creating a bidisperse grain pack and running a uniaxial compaction test on it using LIGGGHTS. Scripts for post-processing (calculating, plotting and visualizing coordination numbers and force chains) are also provided.

cvnd_exercises

Exercise notebooks for CVND.

deep-learning

Repo for the Deep Learning Nanodegree Foundations program.

deeplab_retrain_ade20k_colab

Colaboratory (Jupyter) notebook to retrain model for semantic segmentation in Deeplab, Tensorflow. Initial model is MobileNet or Xception with ADE20K dataset. Derived from Tensorflow official demo.

ds-cheatsheets

List of Data Science Cheatsheets to rule the world

geodatasets

Synthetic datasets for geoscience (geo)statistical modeling

grain-variogram-calculation

This Python 3 script attempts to examine if there are spatial correlations between the different spherical grains in a bidisperse (two-sized) grain pack by constructing variograms for measuring the spatial distribution of grain volumes and the inter-granular distances

home-credit-default-risk-recognition

The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.

ml_sagemaker_studies

Case studies, examples, and exercises for learning to deploy ML models using AWS SageMaker.

mplbm-ut

Library for performing multiphase simulations (based on the Shan-Chen model) in complicated geometries (i.e. porous media 3D images)

mudrocknet

MudrockNet is a deep learning SEM image segmentation model for mudrocks to identify pores and silt size grains, and is based on Google’s DeepLab-v3+ architecture implemented with TensorFlow.

notebooks-contrib

RAPIDS Community Notebooks

sagemaker-deployment

Code and associated files for the deploying ML models within AWS SageMaker

synthetic_well-log_polynomial_regression

This project attempts to construct a missing well log from other available well logs, more specifically an NMR well log from the measured Gamma Ray (GR), Caliper, Resistivity logs and the interpreted porosity from a well.

tensorflow-deeplab-v3-plus

DeepLabv3+ built in TensorFlow

tensorflow-models

Models and examples built with TensorFlow

tmls2020

vtk

Mirror of Visualization Toolkit repository

workshop

AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker