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Dr Amélie Anglade

Dr Amélie Anglade has worked for SoundCloud, Philips and Sony. She is a freelance Data Science Consultant specializing in Music Information Retrieval. Mostly engaged by music startups, she develops solutions for music data ranging from recommender systems and audio signal processing to re-ranking and classification algorithms.
Amélie has a Masters in Computer Science from the École National Supérieure d'Informatique pour l'Industrie et l'Enterprise (Grande École, France) and in Complex Adaptive Systems from Chalmers University of Technology (Sweden). She also holds a PhD in Music Information Retrieval from Queen Mary, University of London. She is a serial volunteer and has been involved with OpenTechSchool, Berlin Geekettes, and Hackership.
http://amelieanglade.net/
https://github.com/utstikkar
https://www.linkedin.com/in/amelieanglade/
 

INTRODUCTION TO PYTHON FOR DATA SCIENCE

Outcome

  • Solid understanding of Python and Pandas and good practices involved.
  • understanding data frames 
  • Data munging and analytics

Content 

A crash course in Python, including the language and its ecosystem, as well as the libraries essential to a Data Scientist.

  • Introduction
    • Graph Theory and Algorithms
    • Network properties and models
    • PageRank Algorithm
    • Graph Computing Technologies
    • Programming project

Python

  • Python for DS Components
  • Python 2 vs. Python 3
  • Installing Python and all useful packages
  • Running the IPython interpreter and a python file
  • Jupyter Notebook
  • Python basics

Pandas

  • Data structures in Pandas
  • Working with dataframes
  • Example: Using pandas on the MovieLens dataset
  • Data Munging with Pandas

Prerequisites

  • Some programming skills (but not necessarily in Python)