[Video]
Python is the most popular computer programming language in the world and it is the standard language used for advanced analytics. The things we will do in this class go far beyond what is possible with Microsoft Excel. We will use a number of tools that are probably new for you. The point is to expose you to the actual tools that people use for business analytics.
Accessing Python on the Cloud:
AWS: you can sign up for a free account with AWS which will allow you to use SageMaker.
Free Jupyter Notebooks from: Google Colab and Microsoft Azure Notebook
On your computer:
Kaggle (use a filter for Python – otherwise you will get notebooks written using other languages like R)
SciPy: SciPy, pronounced “SIGH pi”, is used in mathematics, scientific computing, engineering, and technical computing. SciPy contains varieties of sub packages which help to solve the most common issue related to scientific computation.
collection of things: https://github.com/mdozmorov/DataScience_Python_notes
statistics notes and resources: https://github.com/mdozmorov/Statistics_notes
AirBNB: http://insideairbnb.com/austin/
Stock and Commodities: https://financialmodelingprep.com/ and https://www.quandl.com/tools/python
Financial indicators (FRED): https://fred.stlouisfed.org/docs/api/fred/
- Intro to Statistics with Python, by Thomas Haslwanter.
- Python for Data Analysis, by William McKinney.
- Python Data Science Handbook, by Jake VanderPlas.
- Data Science from Scratch in Python, by Joel Grus.
- Python for Finance, by Yves Hilpisch. Git Repo
- Mastering Python for Finance, by James Ma Weiming. Git Repo
- Python Finance Cookbook, by Eryk Lewinson. Git Repo