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120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

adaptive_binning_chisquared_2sam

This repository contains a 2 sample chi squared test the uses adaptive binning using the approach of Roederer et al. (http://onlinelibrary.wiley.com/doi/10.1002/1097-0320(20010901)45:1%3C47::AID-CYTO1143%3E3.0.CO;2-A/epdf)

ai-feynman

autoencoder_demonstration

Demonstrating the workings of an autoencoder. A dataframe of n independent and m dependent variables is constructed and the autoencoder performs well when the encoding dimension is n or larger.

bayesnetbucketelim

Solving Bayesian Network Inference with Bucket Elimination

data_exploration_game

Navigate through a high dimensional data set

dl_resources

A list of Deep Learning resources

eta_to_ap_gamma_search

LHCb search for eta decaying to a photon and a dark photon (A'), which itself decays into two muons

functionscaler

Given a discrete probability density function learn a function that turns samples from the pdf into samples from desired distribution.

heptools

A collection of tools that are helpful to me during my PhD in Particle Physics at MIT

interpreting-cnn-for-text_adversarial

jets

learningml

This repository demonstrates how to make a project pip installable, write a Python module in C++ and use scikit-learn, keras and spearmint

lhcb_pid_compression

A benchmark to the challenge of compressing an obscured dataset containing Particle Identification

lhcbpvfinding

Track reconstruction for the LHCb experiment at CERN: Finding the primary vertices for particle physics events in the VertexLocator (Velo) detector

mickypaganini.github.io

minimal_glo

Minimal PyTorch implementation of Generative Latent Optimization from the paper "Optimizing the Latent Space of Generative Networks"

minortofatal

Minor to Fatal: Predicting Injury Severity in Traffic Data - Project for 15.071 at MIT

mitjuniorlab

Some Jupyter notebook examples for data analysis

mltools

This python based project is aimed at building a coherent framework of Machine Learning Tools for Particle and Nuclear Physics. It uses scikit-learn, tensorflow and MOE and depends on hep_ml.

n-beats

Pytorch/Keras implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

nltk

NLTK Source

pokerbot

randomnumbergenerator_os_x_app

This is a very easy example of how to create a visual OS X app using python tkinter and py2app.

saelens

Training Sparse Autoencoders on Language Models

spearmint_wrapper

A wrapper around the spearmint gaussian process to optimise hyperparameters for skearn, xgboost and keras

supply-distribution_chain_dartboard

Supply/Distribution Chain Planning at Dartboard Corporation : Case study

unbiasedml

Investigating how to train a classifier such that no peaking structure is induced in the spectrum of control variables

weissercn-github.io

Constantin's personal website

weissercn.github.io

Constantin Weisser's website