SajadAzami / python-datamining-workshop

Python Workshop, An Intorduction to Data Analysis with Python

python-datamining-workshop

Python Workshop, CEIT-SSC Workshops, September 2017

An Intorduction to Data Analysis with Python

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
  • Dataframes
  • Multi Level Indices
  • Aggregation
  • Working with Large Datasets

• Introduction to Scipy Stats:

  • Continuous and Discrete Distributions
  • Useful Functions for Statistical Experiments

• Introduction to Scikit:

  • Machine Learning Concepts Review
  • Preprocessing
  • Model Training with Scikit
  • Testing the Model
  • Evaluation Methods
  • Useful Functions for Model Selection
  • Model Persistence

• Models:

  • Preprocessing Methods
  • Classification Models
  • Regression Models
  • Clustering
  • Dimensionality Reduction
  • Bayesian Nets
  • Neural Nets

• Datamining Competitions:

  • A Framework for Teams
  • DMC17 Experiences
  • Dos and Don'ts

• Examples:

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