Michael's repositories
awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
data-science-blogs
A curated list of data science blogs
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
data-scientist-roadmap
Toturials coming with the "data science roadmap" picture.
DataScienceResources
Open Source Data Science Resources.
LearnDataScience
Open Content for self-directed learning in data science
LSSTC-DSFP-Sessions
Lecture slides, Jupyter notebooks, and other material from the LSSTC Data Science Fellowship Program
Machine-learning-examples
Contains machine learning examples obtained online
photometry_with_sextractor
Basic differential photometry using sextractor
photometrypipeline
automated photometry pipeline for small to medium-sized observatories
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 ;)
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
SAAO_Postgrad_Tools
This contains codes written by students to aid in their everyday analysis of data
spark-notebook
Interactive and Reactive Data Science using Scala and Spark.
specreduce
Tools for the reduction of spectroscopic observations from Optical and NIR instruments
stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.