Channels

Channels

Notes

• We do not have channels specific to the projects! The goal of this decision is to encourage broad discussion on theories, topics and ideas. It is totally OK to ask project specific questions in appropriate theory channels (supervised, unsupervised, reinforcement learning), we just don’t want to focus solely on the projects in our conversations.
• We have a fair amount of channels. Join the ones you are interested in. Every channel has a purpose and description. If you think we need a new channel, please request it in #to_admin

Base Channels

• #announcements
  • Reserved for official announcements from Udacity and student admins. Only Udacity and student admins can post here
• #careers
  • For discussion about resumes, interviews, and jobs
• #code
  • Primarily for getting help with bugs in your code that have you stuck, but also a good place to discuss code practices and general questions about programming
• #experience-feedback
  • Share with Udacity your experience in the program and provide helpful feedback which can be used to improve the content and projects! Udacity staff will monitor this channel, so please be professional!
• #first-week-experience
  • Share your experience as you start out the Nanodegree, and if you have questions about the program that your fellow students might be able to answer, ask away!
• #general
  • General discussion of the MLND program among students
• #ml-capstone
  • Discuss among students your ideas, challenges, and interesting problems related to your capstone research (whether you've started the project already or just want to discuss an idea for one)
• #ml-deep-learning
  • Discuss among students any questions, observations, or interesting information related to Deep Learning and the program content
• ml-intro-content
  • Discuss among students any questions, observations, or interesting information related to the First Week Experience materials and the program content
• #ml-model-validation
  • Discuss among students any questions, observations, or interesting information related to Model Evaluation and Validation and the program content
• #ml-reinforcement
  • Discuss among students any questions, observations, or interesting information related to Reinforcement Learning and the program content
• #ml-supervised
  • Discuss among students any questions, observations, or interesting information related to Supervised Learning and the program content
• #ml-unsupervised
  • Discuss among students any questions, observations, or interesting information related to Unsupervised Learning and the program content
• #random
  • A place for non-work-related flimflam, faffing, hodge-podge or jibber-jabber you'd prefer to keep out of more focused work-related channels

Extras

• #bigdata
  • For discussion of the unique problems that come with data too large to fit into memory on a single machine. Also includes discussions of Hadoop and Spark.
• #datawrangling
  • For discussion of the most time consuming of data science / machine learning tasks: cleaning and structuring data
• #deploy
  • Discuss how to make your ML project usable by other people. Mostly web-related discussion here, but anything that fits the word #deploy is really OK.
• #hardware
  • What rig? What GPU? How much ram? You name it, we'll talk about it.
• #ideas
  • Have an idea for a cool new project or real-world application of machine learning and AI? Share it with us here and start a discussion!
• #kaggle
  • Discuss kaggle competitions and form teams.
• #math
  • As machine learning people, we all have an interest in math; discuss mathematical topics that lie outside the scope of the Nanodegree here
• #mit_1806
  • Started by fellow student Joshua Cook, a group of Nanodegree students have been working through the MIT OCW course in Linear Algebra by Gilbert Strang, called 18.06; this channel is for discussion amongst this group, which all are welcome to join
• #ml-reads
  • A place to post and discuss any interesting articles, papers, books, etc. related to machine learning and AI
• #nlp
  • All things Natural Language Processing, may have some overlap with deep learning (recurrent neural networks), feel free to discuss DL bits in either channel.
• #to_admin
  • For questions, comments, concerns addressed to the student admins of the Slack team
• #visualization
  • To discuss and get feedback on your visualizations

Archived Channels

• #ask-alumni
  • Archived: Ask recent graduates and alumni about their experiences in the program!

Final Note:

• If you ask a question in a channel but aren’t getting a response, make sure that there are people in the channel. It’s ok to @mention someone if you’d like to ask them to the join the channel to help with the discussion (@mention will automatically invite them into the channel). If you are still stuck and not getting help, try #general, but be prepared for others to tell you “sorry, I don’t have time”, or “I don’t know”