Python & Machine Learning Bootcamp 2.0

Full course name: Python & Machine Learning Bootcamp 2.0: Regression Algorithms

This bootcamp is the continuation of the Python and Machine Learning 1.0: Data Cleaning & Classification. The bootcamp will provide hands-on experience for building regression models using machine learning algorithms. Students will explore and visualize data with the Matplotlib package. The workshop will cover a variety of regression techniques including feature selection and regularization. The regression techniques will be implemented in Python to test, measure, and implement various machine learning models.

The bootcamp is for analysts, product managers, mathematicians, business managers, or anyone else that wants to learn how to build predictive models and visualize data in Python.

The workshop is very practical and hands-on with lots of exercises. You'll build your own library of Python scripts that can be reused after your done with the bootcamp. Students will have the skills to implement regression models and make predictions by the end of the bootcamp.

Day 1

• Data exploration with the Pandas Package
• Data visualization with the Matplotlib Package
• Regression modeling overview
• Ordinary Least Squares
• Root Mean Square Error

Day 2

• Residual Analysis
• Multicollinearity
• Feature Selection
• Model Complexity and Regularization
• Implementing predictive models

Takeaways:

• Visualizing data for analysis
• Select features and machine learning algorithm for models
• Analyze regression results
• Implement predictive models

Prereqs & Preparation:
Students should have completed the Introduction to Python Bootcamp and Python and Machine Learning 1.0: Data Cleaning & Classification.

Equivalent skills include: - If Statements - For Loops - Function Definitions - Variables - Creating and Indexing Lists and Dictionaries - Importing Packages - Intermediate knowledge of the Pandas Package for data exploration and cleaning - Familiarity with the categories of supervised machine learning algorithms and the Scikit-Learn package

You must bring a laptop with a text editor. Students should install Anaconda, which is a free package that includes python and a number of tools that will be used in class (http://continuum.io/downloads).

Advance your learning with General Assembly's Python Programming Course.