abhishekdbihani

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.

ds-cheatsheets

List of Data Science Cheatsheets to rule the world

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.

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.

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.

VTK

Mirror of Visualization Toolkit repository

MPLBM-UT

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

abhishekdbihani/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.

abhishekdbihani/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.

abhishekdbihani/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.

abhishekdbihani/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.

abhishekdbihani/awesome-production-machine-learning

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

abhishekdbihani/ds-cheatsheets

List of Data Science Cheatsheets to rule the world

abhishekdbihani/VTK

Mirror of Visualization Toolkit repository

abhishekdbihani/abhishekdbihani.github.io

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

abhishekdbihani/aws-machine-learning-university-accelerated-cv

Machine Learning University: Accelerated Computer Vision Class

abhishekdbihani/CVND_Exercises

Exercise notebooks for CVND.

abhishekdbihani/deep-learning

Repo for the Deep Learning Nanodegree Foundations program.

abhishekdbihani/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.

abhishekdbihani/GeoDataSets

Synthetic datasets for geoscience (geo)statistical modeling

abhishekdbihani/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

abhishekdbihani/ML_SageMaker_Studies

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

abhishekdbihani/MPLBM-UT

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

abhishekdbihani/notebooks-contrib

RAPIDS Community Notebooks

abhishekdbihani/sagemaker-deployment

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

abhishekdbihani/tensorflow-deeplab-v3-plus

DeepLabv3+ built in TensorFlow

abhishekdbihani/tensorflow-models

Models and examples built with TensorFlow

abhishekdbihani/TMLS2020

abhishekdbihani/workshop

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