# PBL 2.2 - Command Line Lab ### Background Reading * https://www.learnenough.com/command-line-tutorial/basics * https://www.dataquest.io/blog/why-learn-the-command-line/ * [Video Intro](https://www.youtube.com/watch?v=s5S_2BdrMJE) * [More Slides](https://www.slideshare.net/accesstomemory/commandline-101) * [About that Famous Essay (just for fun reading)](https://en.wikipedia.org/wiki/In_the_Beginning..._Was_the_Command_Line) ### CoderSchool Slides and Video * [Slides](https://www.beautiful.ai/player/-M77k8sT-AIoDLMnFntC) * Video Coming Soon ### Cheat Sheet From https://www.git-tower.com/blog/command-line-cheat-sheet/ ![](https://www.git-tower.com/blog/media/pages/posts/command-line-cheat-sheet/1073300074-1589188081/command-line-cheat-sheet-large01.png) ### Lab Instructions here: * [https://github.com/coderschool/clmystery](https://github.com/coderschool/clmystery)
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Day 1: Prompt: I want to create a cool data science project. My skills are in using python and pandas and seaborn. I'd like my project to really stand out and be impressive - I'm going to be presenting it to a panel of judges in a "shark tank" style format. The first step is discovering interesting data to analyze. Act as my data science mentor, and ask a few questions about my personal interests, and in turn suggest 5 great project ideas. Please respond in the following format: Project Title: <title here> Links to datasets to download: <url of first publicly available dataset here> <url of second publicly available dataset here> Hypotheses: <three interesting hypotheses to explore> Synthesis with other datasets: <one interesting way to merge this project with another project on the list, to synthesize data>

5/28/2023
Prework Assignment: Machine Learning

![](https://i.imgur.com/nuNQ55P.png =128x) Introduction and Background Welcome to CoderSchool! It's really exciting to meet you. You're about to join a cool journey into programming. Before we get started, we wanted to give you a quick "prework" assignment to make sure you'll be ready for the course. If you find the assignment too difficult, don't worry - we're here to help. We'll be uploading some guides and material over the following weeks, and we'll also organize some homework help sessions. What You Should Do

6/7/2021
Lab 2: Adding NLP to Your Bot

Some background on how NLP works (not required, but interesting): Video (quick, just watch 60 seconds): https://youtu.be/d4gGtcobq8M?t=110. They are explaining the TF-IDF method (which you can read about here if you're curious: https://en.wikipedia.org/wiki/Tf%E2%80%93idf) Video (broadest): https://www.youtube.com/watch?v=fOvTtapxa9c, slight bit on chatbots at 4:53 Article: https://becominghuman.ai/a-simple-introduction-to-natural-language-processing-ea66a1747b32. Step 0: hit the magic button Go to your settings, and then click "Built-In NLP". For language model, let's default to English, but also include support for Vietnamese.

8/30/2020
Lab 1 - Messenger Platform

Step 0 - Set up Facebook Account https://developers.facebook.com/docs/messenger-platform/getting-started/app-setup You'll need the first three things, which will be self-explanatory. Facebook Page: A Facebook Page will be used as the identity of your Messenger experience. When people chat with your app, they will see the Page name and the Page profile picture. To create a new Page, visit https://www.facebook.com/pages/create Facebook Developer Account: Your developer account is required to create new apps, which are the core of any Facebook integration. You can create a new developer account by going to the Facebook Developers website and clicking the 'Get Started' button. Facebook App: The Facebook app contains the settings for your Messenger experience, including access tokens. To create a new app, visit your app dashboard

8/30/2020
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