readme

README.md

@@ -19,10 +19,50 @@ Show you simple machine learning can actually be, where the real hard part is ac
 
 ## Part 3 - Our Method and where we will be getting our Data
 Cover how to acquire, label and organize data, as well as figure out which machine learning algorithm to use.  
-[Video](https://youtu.be/AleGZ9dkfPs?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3)
+[Video](https://youtu.be/AleGZ9dkfPs?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
 [Text](https://pythonprogramming.net/data-acquisition-machine-learning/)
 
 ## Part 4 - Parsing data
 How to handle our data set for machine learning. Cover basic code regarding how to pull specific data points out of the file.  
-[Video](https://youtu.be/rAdAVcS4aL0?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3)
+[Video](https://youtu.be/rAdAVcS4aL0?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
 [Text](https://pythonprogramming.net/getting-data-machine-learning/?completed=/data-acquisition-machine-learning/)
+
+## Part 5 - More Parsing
+Pulling out the specific data point that we're interested in as using as a feature.
+[Video](https://youtu.be/2vQfMAEu670?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
+[Text](https://pythonprogramming.net/parsing-data-website-machine-learning/)
+
+## Part 6 - More Parsing
+Use the Pandas module to help structure and modify our data.  
+[Video](https://youtu.be/cdaMWZIy5vA?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3)) |
+[Text](https://pythonprogramming.net/using-pandas-structure-process-data/)
+
+## Part 7 - Getting more data and meshing data sets
+Grab S&P 500 index data to use as a benchmark. Label stocks that outperform market or not.  
+[Video](https://youtu.be/PMAwBh0nrds?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
+[Text](https://pythonprogramming.net/getting-data-sp-500-index-value-comparison/)
+
+## Part 8 - Labeling of data part 1
+Label data using the stock price's performance compared to the S&P 500 index's performance.  
+[Video](https://youtu.be/QJKJBVUywDM?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
+[Text](https://pythonprogramming.net/labeling-data-machine-learning/)
+
+## Part 9 - Labeling of data part 2
+Calculate the difference in percent change performance between the individual stocks and the overall S&P 500 index.  
+[Video](https://youtu.be/THOyYh-Bfno?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
+[Text](https://pythonprogramming.net/labeling-data-machine-learning-part-2/)
+
+## Part 10 - More Parsing
+Labeling data as out or under-performing the S&P500.  
+[Video](https://youtu.be/Tk2JfUr6IT4?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
+[Text](https://pythonprogramming.net/label-data-machine-learning/)
+
+## Part 11 - Linear SVC Machine learning SVM example with Python
+Basic linear SVC example with scikit-learn.  
+[Video](https://youtu.be/81ZGOib7DTk?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
+[Text](https://pythonprogramming.net/linear-svc-example-scikit-learn-svm-python/)
+
+## Part 12 - Getting more features from our data
+How to grab more data features from our data set for us to do learning on.
+[Video](https://youtu.be/4WM6hB7l4Lc?list=PLQVvvaa0QuDd0flgGphKCej-9jp-QdzZ3) |
+[Text](https://pythonprogramming.net/collecting-features-machine-learning/)