Tuesday! Hacky Hour! Come along to Hackett Cafe and get help with your coding, your analyis, your bioinformatics or data science problems, and we can see what we'll do! Beginners welcome!!!! There's iced coffee!!!!!!!!
Going forward, I am not sure how much posting here that will happen. If you want to get updates on when @uwanews Hacky Hour is happening, please join the group on LinkedIn: https://t.co/59uMT9lts1
Or follow @JamesPBLloyd over on Blue Sky:
https://t.co/xQ4erAiwnT
Don't forget that we have Hacky Hour at 2pm in Catalyst Cafe to solve all of you computational problems. Guaranteed*
*Guarantee not validate in any Australia state or territory.
@JamesPBLloyd is back from their adventures overseas and will be attending Hacky Hour today at Catalyst cafe at 2pm. Huge thank you for others keeping the Hacky Hour alive while James was traveling (@ClauseLeni and others)
Stop waiting for your code to fix itself and come to Hacky Hour on the UWA Crawley campus (Catalyst cafe) at 2pm for all your coding and data analysis needs!
Come to UWA's Hacky Hour at Catalyst Cafe today at 2pm for all your help with data analysis, coding and using the university's High Performance Computing cluster!
Hacky hour at 2pm today in Catalyst Cafe on Crawley campus of UWA. Come for chats about data analysis, programming issues or how to use high performance computing resources.
Going forward, all Hacky Hours will change from Hackett Cafe to Catalyst Cafe (on UWA Crawley Campus). They remain open during the Semester breaks later and is better for the current cohort of people attending. Apologies for any confusion or inconvenience this causes anyone.
Going forward, all Hacky Hours will change from Hackett Cafe to Catalyst Cafe (on UWA Crawley Campus). They remain open during the Semester breaks later and is better for the current cohort of people attending. Apologies for any confusion or inconvenience this causes anyone.
Going forward, all Hacky Hours will change from Hackett Cafe to Catalyst Cafe (on UWA Crawley Campus). They remain open during the Semester breaks later and is better for the current cohort of people attending. Apologies for any confusion or inconvenience this causes anyone.
A great session discussing how best to plot and represent data from a machine learning approach.
Also how to move gene symbols from one genome version’s gene IDs to another’s.