What do we want to do????

A stock market tracking algorithm

• data analysis
• web dev
• possible deep learning

Web Scraping

• Scripy or JS library What do we do with scraped data?
• Twitter Sentiment analysis is standard
• Scraped market-related data and see if there is a correlation to stock price

General WebDev -- based on technology

• Javascript --> MEAN
• Python --> Flask Django

Stock modeling with language processing WebApp

• Scrape text data to do analysis (NLP --> natural language processing, Frequency-based analysis)
• web-based interface
• Acess to current stock prices and trends
• Sentiment analysis on companies (text field to enter the companies name)
• Track sentiment over time
• Machine Learning/Data Analysis playground for stocks --> (percent certainty of increase or decrease)
• Paper Trading -- no real money

What will we need to learn (General)

-- web scraping (getting data) -- web dev (present data/ have cool features) -- sentiment analysis/NLP/NLU

What will we actually need to learn though

Languages

• Javascript for web dev
• Python for data analysis
• Py/JS for web scraping (scrapy/JSJSJSJSJSJS)

Spesific Libraries

• SCRAPY/JSJSJS for scraping
• MongoDB -- Database for webdev
• Node/Express -- backend
• Angular/React -- frontend
• sklearn -- python machine learning library
• pandas -- data manipulation
• numpy/scipy -- efficient data storage and access
• tensorflow/keras -- deep learning
• NLTK -- natural language tool kit

General

• Cloud service to host (GCP, Heroku, AWS)

How do we approach this

We are going to start with web scraping as a group The future plan is to work through area by area together

Action Items

AP --> Throw tutorials at JT DR and DC JT --> scrapy -- add a file to this repo
DR --> scrapy -- add a file to this repo
DC --> scrapy -- add a file to this repo