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algorithmcurriculum

A basic path to learning algorithms using online courses

argparse.jl

Package for parsing command-line arguments to Julia programs.

bayesian_channel

A prior to channel attribution campaign success

bda_course_aalto

Bayesian Data Analysis course at Aalto

clrs

:notebook:Solutions to Introduction to Algorithms

clrs-1

Some exercises and problems in Introduction to Algorithms 3rd edition.

clsm

coursework

summer school coursework

css2013

Computational Social Science, Applied Mathematics, Columbia University (Spring 2013)

css_project

Arash, Tony Project

ctci-solutions

Python solutions to Cracking the Coding Interview (6th edition)

dep2

disaster_text

text classification framework using various nlp techniques

distributions.jl

A Julia package for probability distributions and associated functions.

disvimmsb

Stochastic Variational Inference MMSB for directed network

dlbook_exercises

Exercises for the Deep Learning textbook at www.deeplearningbook.org

dotfiles

My dotfiles and personal preferences

email-classification

gedit-panel-switcher

Switch panels in gedit with a keyboard shortcut.

is_that_a_duplicate_quora_question

joint_dcdir

joint model with bivariate dirichlet

julia_tutorials

Tutorials on Julia topics

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.

lnmmsb

mcmc_for_ammsb

ml-tutorial

Introduction to ML packages for the 6.86x course

ml_proj_template

mvd

MultiVariateDirichlet

nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more