Welcome to the General Assembly Data Science Handout page. Here I'll be assembling handouts, walkthrough and links for everyone to have some references to follow-up after class.
###General Resources ####Books
- Python for Data Analysis
- Elements of Statistical Learning (great reference for the theory behind a lot of the techniques)
- Machine Learning For Hackers (R code examples and walkthroughs)
###Lesson 1: Introduction to Data Science & Basic Data Manipulation
####Slides
####Handouts
####Links
- How To Start Thinking Like a Data Scientist
- Data Science Workflow
- Video Tutorials for Command Line Basics
- Command Line Data Manipulation
- Git Tutorial from Atlassian
- Git Tutorial from CodeSchool
###Lesson 2: Data Storage and Extraction
####Slides
####Handouts
####Links
- Comparison of NoSQL Databases
- Interactive Python Tutorial
- Introduction to Python
- Python Data Structures
###Lesson 3: Python and Data Manipulation
####Handouts
####Links
###Lesson 4: Data Visualization ####Assignment 1: Due Jan 9
####Handouts
####Slides
####Links
- Linear Algebra in 4 Pages
- Narrative Visualization: Telling Stories With Data
- Bokeh
- Vincent
- Python ggplot
- Matplotlib
####Slides
####Handouts -Sklearn and KNearest Neighbors
####Links
####Handouts -Linear Regression
####Links
####Slides
####Links
- Logistic Regression Walkthrough
- Logistic Regression w/ Statsmodel - Well Switching in Bangledesh
- Odds Ratio Explanation
- Fast Logistic Regression: Mahout
- Fast Logistic Regression: Vowpal Wabbit
- Fast Logistic Regression: LIBLINEAR
####Links