In this part of our machine learning tutorial with scikit-learn and Python, we're covering how to acquire, label and organize our data, as well as figure out which machine learning algorithm to use. Playlist link: https://www.youtube.com/watch?v=URTZ2jKCgBc&list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3&index=3 Flowchart for figuring out which machine learning algorithm to use: http://scikit-learn.org/stable/tutorial/machine_learning_map/index.html To get company data, you can use sec.gov, finance.yahoo.com, or many other locations. To alleviate the need for people to suck up tons of bandwidth, I have compiled and zipped up a sample dataset that is the straight HTML data as if you had parsed Yahoo Finance for over a decade. The location: http://pythonprogramming.net/downloads/intraQuarter.zip sample code: http://pythonprogramming.net http://seaofbtc.com http://sentdex.com http://hkinsley.com https://twitter.com/sentdex Bitcoin donations: 1GV7srgR4NJx4vrk7avCmmVQQrqmv87ty6
Visibility: 36671
Duration: 24m 24s
Rating: 221