Title:

Full Stack Data Science: Building Your First Smart Application

Conference:

PyColorado 2019 Sep 6, 7, 8, 2019 Denver, CO

Talk Format:

Workshop ~ 3 hours

Description:

• Web applications are the way information is delivered, and machine learning systems are frequently driving the decisions behind the applications. As machine learning increasingly becomes a part of the standard tech stack, it is valuable, and perhaps at some future point expected, that data scientists and web developers have an intuition into how the other side works. Join me for a half day workshop and learn how to use the tools of both disciplines together, and build your first smart application.

One Line Summary:

• A two way intro - basic data science/machine learning for developers and basic web development for data scientists.

Who and Why (Audience):

The prospective audience is made up of three groups with different take-aways for each. The first group is beginners. People that use python but are perhaps not employed as developers or data scientists. Part-time developing scientists and students would fall into this category. They will take away an understanding of the ease of building an application in this fashion, plenty of sample code to plug into their own projects, and introduction to a wide variety of packages and concepts.

The second group is data scientists. The will take away an understanding of how to plan, build, and deploy a simple web application to showcase their ds work.

The third group is professional developers. They will have the opportunity to learn about the python scientific and data analysis stack, and how to construct and deploy a machine learning model via a simple application.

I'd expect participants to be comfortable/familiar with the following to get the most out of the workshop:

• Virtual environments
• Using a text editor to write code
• Git/Github
• Working on the command line/basic Linux commands
• The core python 3 language including control flow and common data structures

They should also have:

• A Unix-like system on which to work with the ability to install packages
• Install Instructions

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1. Clone this repo
2. cd into the directory and run ./install.sh
3. After install, execute ./run.sh -r to start the server
4. If Bokeh sample data isn't available in your environment you execute ./run.sh -d to download the sample data