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100-days-of-ml-code

100 Days of ML Coding

120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

2018-machinelearning-lectures-esa

Machine Learning Lectures at the European Space Agency (ESA) in 2018

automated-manual-comparison

Automated vs Manual Feature Engineering Comparison. Implemented using Featuretools.

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

bayesian-stats-modelling-tutorial

How to do Bayesian statistical modelling using numpy and PyMC3

bda_py_demos

Bayesian Data Analysis demos for Python

bmw-tensorflow-training-gui

This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! Training with TensorFlow has never been so easy.

book

cookbook-2nd

IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018

data-science--cheat-sheet

Cheat Sheets

data-science-journal

Personal repository of data science demonstrations and references

datacamp

DataCamp data-science courses

datacamp-community-tutorials

Tutorials for DataCamp (www.datacamp.com)

datacamp-deep-learning

DataCamp's Deep Learning in Python 🐍 & Keras

datascienceresources

Open Source Data Science Resources.

dbda-python

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-ttf

Survival analsyis and time-to-failure predictive modeling using Weibull distributions and Recurrent Neural Networks in Keras

ds-cheatsheets

List of Data Science Cheatsheets to rule the world

elecmetal

hoff-bayesian-statistics

R Markdown notes for Peter D. Hoff, "A First Course in Bayesian Statistical Methods"

imbalanced-data

Notebook implementing techniques discussed in my blog post about imbalanced data.

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries accross different industries.

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.

lifelines

Survival analysis in Python

machine-learning-with-python-cookbook-notes

My jupyter notebooks/code from Chris Albon's Machine Learning with Python Cookbook

machinelearningsamples-predictivemaintenance

MachineLearningSamples-PredictiveMaitenance

medium_python_tutorials

Store the Python code for my tutoials on Medium