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Lecture materials, Python Workshop: An Introduction to Scientific Tools

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python-scientific-tools

Python Workshop, 9th LinuxFest, May 2017

Prerequisites:

  1. Basic understanding of programming
  2. Experience writing code in a modern programming language(C++, Java, JavaScript, Php…)
  3. A system with Python 3 installed(3.4 is preferred)
  4. A text-editor or IDE(PyCharm is preferred)
  5. Basic Knowledge of Machine Learning Concept(Not Necessary)

Headlines:

  • Introduction to NumPy:

    • Python Data Structures
    • Python Containers
    • Introduction to NumPy Package
    • Working with NumPy Arrays
    • Indexing and Slicing
  • Introduction to Plotting Tools:

    • Plotting Data with Matplotlib
    • Smoothing Data in Matplotlib
    • Using Seaborn
  • Introduction to Pandas:

    • Pandas Overview
    • Series in Pandas
    • DataFrames in Pandas
    • Multi Level Indices
    • Aggregation
    • Working with Large Datasets
  • Introduction to Scipy Stats:

    • Continuous and Discrete Distributions
    • Useful Functions for Statistical Experiments
  • Introduction to Scikit:

    • Slight Introduction to Machine Learning
    • Preprocessing
    • Learning a Model with Scikit
    • Testing the Model
    • Evaluation Methods
    • Useful Functions for Model Selection
    • Model Persistence
  • Examples:

    • Word Anagrams with NumPy
    • Baby Names with Pandas
    • A Statistical Simulation
    • Learning and Evaluating Various Models with Scikit

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