Abhishek Bihani's repositories
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.
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.
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.
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.
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
ds-cheatsheets
List of Data Science Cheatsheets to rule the world
abhishekdbihani.github.io
Use this template if you need a quick developer / data science portfolio! Based on a Minimal Jekyll theme for GitHub Pages.
aws-machine-learning-university-accelerated-cv
Machine Learning University: Accelerated Computer Vision Class
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.
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
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)
notebooks-contrib
RAPIDS Community Notebooks
sagemaker-deployment
Code and associated files for the deploying ML models within AWS SageMaker
tensorflow-deeplab-v3-plus
DeepLabv3+ built in TensorFlow
tensorflow-models
Models and examples built with TensorFlow
workshop
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker