Diptanshu Singh (Dipsingh)

Dipsingh

Geek Repo

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Diptanshu Singh's repositories

gobgp

BGP implemented in the Go Programming Language

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algorithms-2

This repository is for learning and understanding how algorithms work.

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AppliedStatisticsForNeuroscience

Materials for UC Berkeley Neuroscience 299

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appliedstats

:bar_chart: Methods of Applied Statistics Course Textbook Repository

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CausalImpact

An R package for causal inference in time series

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COMS4995-s19

COMS W4995 Applied Machine Learning - Spring 19

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gotraining

Go Training Class Material :

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handson-unsupervised-learning

Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)

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IntroStatLearn

Exercises from 'Introduction to Statistical Learning with Applications in R' written in Python.

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ISI_Workshop_2019

Materials for 1-day workshop on high dimensional time series analysis at ISI 2019

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ISL-python

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

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ISLR-python-1

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

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Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

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Machine-Learning

Machine Learning Projects

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machine_learning_refined

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

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mlcourse.ai

Open Machine Learning Course

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mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

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numerical-linear-algebra

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

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pdf-dump

A dump of all the data science materials (mostly pdf's) that I have accumulated over the years

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Practical-Time-Series-Analysis

Practical Time-Series Analysis, published by Packt

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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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programmers-introduction-to-mathematics

Code for A Programmer's Introduction to Mathematics

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ProgrammersIntroMathematics

Programmers Intro to Mathematics Excercises

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random-scripts

Random Stuff

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stat479-machine-learning-fs19

Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison

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statsintro_python

Python modules and IPython Notebooks, for the book "Introduction to Statistics With Python"

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tspreprocess

A Python package to preprocess time series

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