Year in Review

To say 2017 was an interesting year would be quite the understatement.

We saw everything from the explosion of Bitcoin, blockchain and crypto-currencies. Too bad if you didn't get in on the crypto craze before the wave.

We also witnessed the growth and maturity of a several  Deep Learning frameworks:

• Facebook - PyTorch
• Apple -  CoreML
• Uber - Pyro and Michelangelo
• Amazon - Gluon + MXNet
• Google - Tensorflow 
• DeepMind -  Sonnet

We were wowed once again with the Model 3 launch and Tesla Semi / Roadster v2 unveil. And, we got more insights on Model Y and Falcon Heavy launch.

We also witnessed more products and services powered by Deep Learning / AI and more maturity in the different DL / ML frameworks out there. I really do feel a lot of the worthwhile things in the space going forward will be applying these tools and techniques to solving real problems that have real impacts on our lives vs things that just end up in research papers (even though that's important too) and making these tools more accessible.

I'll leave you with a summary of the awesome things other folks did in 2017

• A Year in Computer Vision by M Tank
• Deep Learning Achievements Over the past Year by Eduard Tyantov
• AI and Deep Learning in 2017 – A Year in Review by WILDML
• A non-comprehensive list of awesome things other people did in 2017 by Jeff Leek
• Interesting ML projects from 2017
• NIPS 2017 notes 

Year in Review

It's been quite an interesting year to say the least.

Lots of new Machine Learning and Deep Learning tools and libraries were released into the wild reducing the barriers to entry.

I'm really hoping to turn a corner and do more writing next year. I just can't seem to be able to shake off my writer's block.

Here again is Jeff Leek's Non-comprehensive list of awesome things other people did in 2016

Year in Review

It's been quite a year.

It appears we're moving closer to the Hardware + Software + AI singularity and all the stuff that comes with that... and it's kind of scary.

Here again is Jeff Leek's Non-comprehensive list of awesome things other people did in 2015.

Some of the majors like Google, Facebook, Baidu and Microsoft open sourced some of their internal Deep Learning tools / frameworks. Most of the value coming from these tools will be interesting and useful products built with / on them.

Also, this one literally sent chills down my spine - Landing of Falcon 9 first stage. I guess we're one step closer to Mars and becoming a multi planetary species.

I didn't quite put out much content out there this year. I'm hoping to do more writing next year.

Stay tuned...

Year in Review

It's been a really interesting year.. I moved to the Bay Area. It's one thing to read about Silicon Valley or visit briefly. It's another to actually live out here and experience all it has to offer. This is the center of this data revolution everyone seems to be talking about. Obviously, if you can manage the ridiculously expensive housing out here and how much more expensive everything is out here, then you should be fine.

To wrap up the year, here is Jeff Leeks' Non-comprehensive list of awesome things other people did in 2014 . It has an rlang slant since he's a statistician.

I had more blog posts and traffic this year than each of the previous 3 year combined. Hoping this trend continues. Just looking at my traffic, it does appear there is a lot more interest in Data Science Education and immersive experiences like boot camps.

Going forward, I plan to do more tutorial style posts showing side projects or other interesting tech I encounter. 

I do want to spend more time delving into Deep Learning. Starting with the nuts and bolts and then moving to available libraries / implementations and sharing some of what I learn along the way... stay tuned