It's new years eve and - as always - I try to finish some things and have some plans for next year.
Review of 2018
Not a lot happened about which I want to write publicly, so here are some other mentionable facts:
- ML-KA is still active.
- I have 40 583 points on StackOverflow and reached 22.4 million people with my posts (source).
- I wrote only 48 articles for this blog (including this one, not counting 13 ones which were pulished yesterday) in 2018. A couple
of them might be interesting:
- Datetime - or even better my short summary What every developer should know about time
- A couple about details in Python such as packaging, str vs repr, property, testing, style guide
- A couple of shorter data science related ones, such as an overview, a project guide, the problems of Feature Importance, time series forecasting
- Only one recipe!
- I've uploaded 195 files to Wikipedia Commons in 2018 (2164 files in total, source). My uploads to Wikipedia Commons are about 6 GiB in total now. On commons, I made 5333 edits in total.
Interesting changes in my life:
- I moved within Munich on 01.06.2017
- Found a couple of new friends 🙂
Overall, I have to say that I spent a lot of time with working. Maybe too much time. I've noticed that I contributed a lot less to Wikipedia, wrote less blog articles of lower quality and spent less time on StackOverflow.
Old year resolutions
- ✗ Participate in a Flashmob
- ✔ Visiting a new country - I've been in the Czech Republic
Old year predictions
I forgot to make predictions last year 😨
New year resolutions
The plans for my new year are:
- [ ] Get comfortable with Orange Bouldering routes (5c-6c) and finish at least 5 harder ones (6c - 7b)… yes, I'm aware that I had exactly that already. I wasn't bouldering for a while. I miss it.
- [ ] Create a GAN for my HASYv2 dataset
- [ ] Create at least 10 more blog posts with recipes: 1, 2
- [ ] Create at least 10 high-quality Media files for Wikipedia: 1
I always do some cleanup before the new year begins. This means especially cleaning my computer stuff of unnecessary trash.
- ✓ Deleting several hundret E-mails (over 500 unread e-mails, 824 starred e-mails)
- [ ] Clean up my smartphones TODO list.
- [ ] Clean up my Desktop / Download folder.
- ✓ Make Backup of Google+ and Gmail (takeout), WhatsApp (tutorial), Amazon, Banking. I skipped Facebook (tutorial) and Twitter (tutorial) this year.
- ✓ Push git stuff
- [ ] Remove things from my YouTube "Watch Later" list
Predictions for 2019
Machine Learning and Technology
- Tensorflow will keep being the dominant deep learning framework as measured by (1) StackOverflow questions, (2) Google Trend, (3) Github repositories
- There will still not be a DOTA playing AI which can replace a human DOTA player in a human team with the usual flexibility.
- We will see fraud cases related to ML (e.g. using speech synthesis for identity theft or tricking a ML system)
- I will come back well from Nepal.
- I will write at least 10 summaries of papers on cs.CV.
- I will learn and fully understand how Flask Blueprints work.
- I will reach level 5 on the first 15 lessons for Spanish on Duolingo and level 3 on the next 13 ones. (So far: 6 on Level 5, 8 on Level 3)
The bigger Picture: Politics, Nature and the World
- There will be over 250 mass shootings in the US in 2019. I define a mass shooting as anything where at least 4 people get injured by a gun. (List of mass shootings in the United States in 2019)
- The government shutdown will last at least 20 days, but no more than 40 days. ✔
- Trump will still be in office
There are also a couple of predictions which I don't know how to check, e.g.
- The hype of Machine Learning and data science will go down a bit as companies are faced with problems / the reality. It will still be important, though.
- Amazing results by GANs. Large Scale Gan Training for High Fidelity Natural Image Synthesis is already pretty awesome. I expect more of this, easier to use for non-ml developers.