Strike Three! 84% Chance that was a Slider
I used TensorFlow to classify baseball pitches. Here’s the backstory! Alternatively, you can skip straight to the Jupyter notebook.
In Transit
I used TensorFlow to classify baseball pitches. Here’s the backstory! Alternatively, you can skip straight to the Jupyter notebook.
A train to the future grounds me in the present.
I was churning through a lot of sources. In the summer of 2017, I was new to New York and frantically learning everything I could about the MTA. After a few months, I had a better grasp on how the capital program functions and a blog post on fare increases. Along the way, my process was a rollercoaster.
One of my February goals is to go on a photo shoot in the city. Save for one family party, I had not used my Nikon DSLR in more than two years. Put another way, I had yet to use my camera my favorite city. I took a few hours this afternoon to fix this.
I am a big fan of polymorphic code. My current mantra is “our code should do one thing, it may just behave differently sometimes.” Towards this end, I often write classes that implement a common interface (that is, same methods and same signatures on those methods).
Last Wednesday, I rode the Amtrak Northeast Regional to our nation’s capital to attend my first Transportation Techies meetup! Michael had been urging me to attend since we first met at TransportationCamp Colorado 2016. Now that I’m on the east coast, it was an easy trip!
A few weeks ago, I was playing around comparing the MTA fares figures against annual inflation. The results initially seemed like some solid clickbait: “MTA Fares Rise Twice As Fast As Inflation.“ I showed one of my coworkers the graph and his reaction was interesting, something along the lines of, “Oh, so now they’re just raking in the money?” Well, not quite. Transit fare increases are a complicated topic and his misunderstanding is 100% justified. I decided to delve deeper into the topic.
This is the third post diving into the graph structure of the New York City subway system. Read the first two for more background!
This post is the second of three four looking into the graph structure of the New York City subway system. In the previous post, I discussed a frontend I built to visualize a depth-first search, breadth-first search, and shortest path algorithm. I ended with a discussion of centrality algorithms. We pick up our hero there…
I’ve been away from the blogging world for a while! The last few months included a fantastic and inspiring trip to Transportation Camp NYC and loads of (mostly) fun weekend work on transit graphs.
I’m a few months late on this one, but I recently wanted to learn about WebSockets and GTFS-realtime feeds. The result: a real-time Boston transit map! I apologize if you were expecting a historical reenactment.
I attended the inaugural TransportationCamp Colorado was last week! Sticking with the format of an “unconference,” attendees were encouraged to propose their own sessions to present their work and/or lead discussions. I took them up on the format and presented the following slides on Transitland and how I used it to create my New York City transit frequency visualization. We had a really great interactive session with many good ideas exchanged!
Friday was a celebration worthy of Duke Ellington and John Hickenlooper. “Take the ‘A’ Train” was finally a meaningful phrase for the Denver metro area! Unfortunately, only one of them could make an appearance, while the other’s legacy lives on. Relive the opening of the RTD University of Colorado A Line with my photo journey below!
Since I detailed my New York City transit frequency visualization project last month, there have been a few updates. Check out the web tool to view the changes!
Transit fans be warned: the Fort Collins streetcar is adorable. It’s no kitten, but Car 21 certainly takes you to an era bygone. I wanted to grab an evening post, tighten the top button on my overcoat, and ride into a romanticized time as I leaned against the rattan-backed seat.
I published my first Ruby gem: gtfs-geojson! You can view the source on GitHub. gtfs-geojson is a Ruby utility to convert a GTFS feed to a GeoJSON file. It’s a simple endeavor, for sure, but I’m pleased with what I learned along the way.
After seeing a call for volunteers in the Coloradoan, Calvin and I are now conductors-in-training for the Fort Collins Municipal Railway! We had our first session yesterday and toured the trolley barn on N. Howes Street. I’ve shared a few photos below!
If you wanted to see pictures of all six eight nine Transfort MAX buses, you are in luck! Please join me as we tour the fleet of North American Bus Industries vehicles. And no, I’m not the first person to practice bus spotting.
Each February, a few Purdue friends and I make our way to Navy Pier for Cider Summit Chicago. This was our third year of sampling fermented apples, and my second of making the weekend trip from Colorado to Chicago. I’ve included a few photos from the fantastic weekend below! They can be reasonably categorized into the following: airports, Chicago, Chicago transit, friends, friends on transit, transit in airports, and waffles.
Update 3/29/16: The transit visualization has been updated! The technical details in this post are still relevant, but some of the conclusions are no longer valid. Read about the updates here!
I like baseball. I like stadiums. I like maps. I really like transit. The result: the Baseball Transit Authority!
To better understand the Fort Collins population and what percentage of it is adequately served by Transfort bus stops, I decided to jump on board the GIS-hype train. I downloaded QGIS, read a bit at qgistutorials.com, and felt ready to dive in.
Rapid transit is coming to Hawaii! Construction has begun on an elevated Honolulu rapid transit system, operated by the Honolulu Authority for Rapid Transit. Residents and tourists alike will be able to traverse a 20-mile route in just 42 minutes.
Most days, I am content to take the bus to work and back, read a piece or two of transit news, and go to sleep dreaming I am swaying in the center aisle of a brisk underground train. Other days, I have an idea that reroutes the temporary flow of my daily consciousness for the better. One Sunday afternoon a few weeks ago, I had one of those thoughts. “I SHOULD RIDE THE ENTIRE DENVER LIGHT RAIL IN ONE DAY.” It seemed so obvious. How was this a new thought to me?! Having completed a similar urban challenge in the past and enjoying a growing passion for public transit, this was the perfect goal. I set a due date: by the end of 2015, I would ride all 6 lines of the RTD light rail.
This essay describes my experience sitting on the boardwalk at Toronto’s Woodbine Beach on Tuesday, September 22, 2015. I was visiting the city to attend a Blue Jays game and appreciate their transit, but I took the following hour or so out of the week to take in my surroundings.
Do you know how many Starbucks locations are contained within the Loop? The gourmet coffee chain’s prevalence inside this 0.24 square mile area of Chicago’s business district gives new meaning to the phrase “on every corner”. On Wednesday afternoon, March, 19th, 2014, Pushpinder, Dhawal, and I set out to take a #selfie in front of all 18. That’s right: one eight.