Berlin Enterprise AI

Enterprise AI isn't about demo day — it's about deployment day.
We're a community for practitioners building, deploying, and scaling AI inside enterprises. Not proofs-of-concept that gather dust. Not buzzwords. Not slideware. We're here to tackle the hard problems: integration, deploying, governance, monitoring, security, ROI, and the messy middle between pilot and production.
We regularly invite tech leads, engineers, data scientists, and decision-makers from enterprises to:

• Learn from practitioners who've shipped AI at scale
• Share the hard-earned lessons — what broke, what worked, what they'd do differently
• Showcase real solutions to real enterprise problems

You belong here if you're:

• A developer, engineer, or data scientist building AI into enterprise systems
• A tech lead or architect designing AI infrastructure and pipelines
• A tech decision-maker evaluating, adopting, or governing AI in your organization
• Anyone who wants to move beyond the hype and learn what actually works in production

If you’d like to speak at our meetups, co-host your events, or inquire about partnership opportunities, please feel free to reach out to us.
https://www.aicamp.ai

If you're game you should have at least completed 1+ ML course, implemented some algorithms or have experience with one of the disciplines above so you can contribute to the group. (~~ beginner/intermediate skill level)
We will use Python.
Hope to see you soon,
Markus
Good Resources – all you need is Jeremy Howard (and Love):
Fast.ai (ML for coders) is by orders of magnitude!! better and more up to date than anything else. Jeremy Howard is the most practical and legit guy in the field. He was Chief Scientist at Kaggle, founded a few  other startups and is a great teacher. 
This one just came out in September 2018: http://www.fast.ai/2018/09/26/ml-launch/ and it is amazing. Or do the Deep Learning 2018 course for images and so on.
Refresher / Lookup on python / pandas
https://github.com/jakevdp/PythonDataScienc...
Only use as reference, not as homework.
Meh/Solala Resources
for Mobile or Ubahn boredom: Brilliant.org (math, lin alg and ML quizzes) – most paid quizzes are sh%t, but 1/3 are well done.
Bad Resources. DON'T WASTE YOUR TIME THERE:
BAD: datacamp.com ('Interactive copy paste with 100% irrelevance to any real world problem taught by people after at least one stroke')
BAD: Andrew Ng's Coursera course. Dated, pedagogically inferior and not pragmatic. You'll finish it and won't be able to do anything after...