Build a Web Application with Python, Flask and NLP
- Basic knowledge of Python, HTML, and Jupyter notebooks
- Ability to install Python libraries as required per course (pip install or however you do it on your OS)
Let's share the wonderful joy of famous quotes to the world with a quoting machine web application that uses natural language sentiment to tailor the right quote for the user.
The class will teach you how to take your Python ideas and extend them to the web into real Web Applications so the world can enjoy your work.
In this class, we will:
develop our ideas in a local Jupyter notebook
gather data (famous quotes)
use the Vader NLP sentiment algorithm
tune our models and dispensing mechanisms locally
design the look and feel
extend responsive HTML templates
port to the web using PythonAnywhere
enjoy great quotes in tune with our moods 24/7
Above all, you will understand how you can port your own Python ideas to the web into fully interactive web applications so the world can enjoy your work!
- Anybody wanting to extend their programmatic reach
- Anybody wanting to share their work to the entire world by porting to the web
- Questions Before Starting Any Project/Software Journey08:31
- Finding Data - Where to Find Famous Quotes08:28
- Sentiment Scoring With the NLTK Vader Tool11:31
- Building the Quote Dispensing Engine - Abstracting With Functions13:26
- A Few Good Tools to Design a Web Application09:51
- A Flask primer16:55
- Getting Professional Help - How I Do It With UpWork10:29
- Building Our Quoting Machine on PythonAnywhere - Part 113:34
- Building Our Quoting Machine on PythonAnywhere - Part 213:18
Data scientist with over 20-years experience in the tech industry, MAs in Predictive Analytics and International Administration, author of Monetizing Machine Learning and The Little Book of Fundamental Indicators, founder of FastML, reached top 1% on Kaggle and awarded "Competitions Expert" title, taught over 20,000 students on Udemy and VP of Data Science at SpringML.
From consulting in machine learning, healthcare modeling, 6 years on Wall Street in the financial industry, and 4 years at Microsoft, I feel like I’ve seen it all. And this has opened my eyes to the huge gap in educational material on applied data science. Like I say:
"It just ain’t real 'til it reaches your customer’s plate"
I am a startup advisor and available for speaking engagements with companies and schools on topics around building and motivating data science teams, and all things applied to machine learning.
Reach me at email@example.com