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ml-presenting's Introduction

Basic Web Development at Lambda School

You might have noticed, the web is an important part of our industry. Medium posts, data visualization, colaborative environments, software libraries, new research, and so much more are all available directly on the web. You haven't entered Machine Learning through the "traditional" 12+ year academic path, and in many ways this is a blessing for your career. Instead of focusing on historical and hidden academic disciplines, you can dive right into the most visible and most relevant material of today.

This also means that you should be presenting yourself using the most visible and relevant material. Today's coding challenge is your first lesson on building your resume on the web.

Starting today, we'll be performing all of our research with the question, "How can I publish this to the internet?" in the back of our heads.

Web deployment

1. Create an account at Github if you don't already have one

2. Fork this repository.

Download your fork to your computer. Git provides numerous methods to do so, depending on your platform.

3. Clone the repository to your computer.

git clone [email protected]:<your username>/ML-Presenting.git

4. Update the file index.html according to the instructions contained therein

Your goal: Draw a dynamic graph in a web page using the data we generated about random vector distances as dimensionality increases.

5. Create an account at netlify:

netlify

Choose "Get started for free" and create an account at netlify. Use your Github account as your signup.

Follow the instructions to deploy the github repository that you just created and modified. Follow the url to your first website!

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