Next week I’ll be demoing Data Scientist Workbench at Spark Summit East (official site) in New York. Polong Lin will be there with me. Come by the expo floor next Wednesday and Thursday and chat with us.
Data Scientist Workbench is what my team builds. It hosts open source data science tools like Jupyter, OpenRefine, R Studio IDE, Zeppelin and others for you. There’s exciting stuff in the changelog every week.
I signed up in time to get into a training session at Spark Summit East, so I’ll be spending my Tuesday working with the Wikipedia data sets. In today’s industry jargon, I’m more of a data engineer than a data scientist, so I’m hoping my Spark skills are up to the level needed for the advanced course.
This week I’m at Datapalooza Seattle, which is a good opportunity to brush up and expand those same Spark skills. In fact, we just posted the Day 1 challenge for Datapalooza. If you’re following along at home, fire up your Data Scientist Workbench, open a Jupyter notebook, and give it a try.
On February 9 through 11, I’ll be mentoring hackers and budding data scientists at Galvanize during Datapalooza Seattle. It should be a great conference covering topics like things like machine learning, natural language processing, and data engineering infrastructure.
Last year’s Datapalooza in San Francisco was a fantastic event with lots of in-depth sessions. I was impressed with the range of material on data science and data engineering. The upcoming Datapalooza Seattle looks equally as fascinating.
My team at work runs Data Scientist Workbench which is free hosted suite of open source tools including Jupyter, Zeppelin, R Studio IDE, and OpenRefine. We also organize free data science education through Big Data University.
I’m expecting Antonio Cangiano, Polong Lin, and Leon Katsnelson to be at Datapalooza with me as fellow mentors.
Let me know if you’re in Seattle at the same time and we’ll connect.
I’ll be teaching two hands-on labs at Insight 2015 in Las Vegas:
LCD-3459 Introduction to Data Science
Data science is a very popular job profile and in great demand in a wide variety of industries. You no longer need a Ph.D. in mathematics or statistics to become a data scientist. Any data professional can upgrade their skills and study data science. This lab introduces the basic concepts of data science and provides hands-on examples to help you apply these concepts.
Update: Do the Intro to Data Science Lab on Big Data University
LCD-3479 Fundamentals of Spark
Spark is one of the most important technologies for big data analytics and Spark skills are in great demand. This lab session introduces Spark fundamentals and applies the concepts using hands-on examples with a Spark cluster in cloud. You can also download a Docker image to your own laptop and run the lab projects there.
Update: Do the Fundamentals of Spark Lab on Big Data University
If you can’t make it, you can teach yourself data science at your own pace at BigDataUniversity.com
I’ve just migrated to a new Macbook Pro as my primary work machine. As part of setting it up, I installed the following:
- Caffeine to prevent it from going to sleep when I don’t want it to go to sleep
- BetterTouchTool so that I can middle-click (three finger tap) to close tabs and paste in the terminal
- f.lux to reduce eye-strain at night
- Firefox as my web browser
- Chrome so that I can run Authy for two-factor authentication on the desktop
- Ditto for running Google Hangouts
- iTerm2 as a superior, multi-pane terminal
- Atom because it’s handy to have a text editor
- Homebrew as an excellent package manager for installing Unix services and tools
- Divvy for resizing windows to fractions of the screen
I’ve experienced increasingly bad wifi performance on my Macbook Air over time. This has been accentuated further by me being somewhere with a lot of network lag. I did some research and the following suggestions made the wifi faster and more responsive with Mac OS 10.10.3 Yosemite.
1. Disable Bluetooth. I don’t use any wireless mice/keyboard/headsets, so Bluetooth doesn’t do anything for me.
2. Disable Facetime. Command+Space, Facetime. File > Preferences > [ ] Enable this account. I’ve never used Facetime, but from what I understand it’s Apple’s clone of Skype that only works with other Apple users.
3. Disable Handoff. System Preferences > General > [ ] Allow Handoff between this Mac and your iCloud devices. Handoff is Apple’s recent attempt to increase platform lock-in for those unfortunate souls who use non-Macbook Apple devices. Seemingly, it negatively affects network performance.
These three steps noticeably improved my wifi performance.
If that doesn’t help, there are more involved things you can do to tune Yosemite wifi performance or work around other Yosemite bugs.
I, for one, look forward to the forthcoming release of Mac OS 10.11 El Capitan.
I’m at the Data Unconference in Toronto today. Jarred Gaertner just gave a through-provoking keynote on the ethics of big data, and I’m about to dig my hands into some open data sets in Richard Pietro’s hands-on session.
My colleague Polong Lin will be on a panel about IBM’s data science tools this afternoon, which should be interesting if only because it’s hard to keep track of everything that’s out there.
#DUTO2015 is sponsored by my friends at Big Data University
I’ll be in San Francisco this weekend helping run the Apache Spark hackathon, and afterwards I’ll be at Spark Summit 2015.
If you’re curious at all about Spark, you should come out and hack with us. We’ll have some fun data sets and help you find a team.
You can take the free Spark Fundamentals course on Big Data University to brush up on your Spark skills. Spark is a framework for fast in-memory and batch analytics processing. It’s algorithmically smarter and so a lot faster than traditional Hadoop.
There’s $10k in prizes at the hackathon.