Nitin Bhushan (nbhushan)

nbhushan

Geek Repo

Company:@godatadriven

Home Page:https://nbhushan.github.io

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Nitin Bhushan's repositories

sequence-modelling

Quasi Deterministic extension to the hidden Markov model for time-series and sequence modelling.

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SlimDashboard

Web application to visualise and analyse high frequency (~1s) sensor data.

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banijay-streamlit-app

app to engage stakeholders

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causal-discovery

Causal discovery methods: simulation study and empirical applications

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causalgraphicalmodels

Causal Graphical Models in Python

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data-science-slidedecks

Slide decks illustrating various topics in data science and AI without complex jargon and unnecessary math

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generalised-additive-models

Generalised additive models (think deep learning, but interpretable)

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python-poetry-CI-template

template repo to build python projects

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AutoEq

Automatic headphone equalization from frequency responses

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awesome-machine-learning-interpretability

A curated list of awesome machine learning interpretability resources.

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CD4ML-Scenarios

Repository with sample code and instructions for "Continuous Intelligence" and "Continuous Delivery for Machine Learning: CD4ML" workshops

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CloudComparer

Compare the various managed cloud services offered by the major public cloud providers in the market.

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forecasting

Time Series Forecasting Best Practices & Examples

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Gaussian-Graphical-Models

An introduction to graphical models in psychometrics.

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jekyll-ideal-image-slider-include

Add image sliders to Jekyll with Ideal Image Slider. HTML include version. Github Pages compatible. (This repository is archived. Issues are disabled. Pull requests will be ignored.)

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M6-methods

Data, Benchmarks, and methods submitted to the M6 forecasting competition

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ml-app-template

An ML project template with sensible defaults

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nbhushan

✨special ✨ repository to add a README.md

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nbhushan-cv

Overleaf CV template

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nbhushan.github.io

A content-first, sliding sidebar theme for Jekyll. [forked]

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openai-quickstart-python

Python example app from the OpenAI API quickstart tutorial

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Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

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pytudes

Python programs, usually short, of considerable difficulty, to perfect particular skills.

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scikit-learn

scikit-learn: machine learning in Python (glemaitre features)

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WhatTheHack

A collection of challenge based hack-a-thons including student guide, coach guide, lecture presentations, sample/instructional code and templates. Please visit the What The Hack website at: https://aka.ms/wth

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WhirlwindTourOfPython

The Jupyter Notebooks behind my OReilly report, "A Whirlwind Tour of Python"

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whisper

Robust Speech Recognition via Large-Scale Weak Supervision

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