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