Category: Unknown Code Ramblings

Seth Jaurez Presenting “Deep Learning for Computer Vision with Applications for Wildlife Conservation”

UPDATED: Video Added from the Conference!

seth-juarezIntroducing Seth Jaurez > @sethjuarez < presenting “Deep Learning for Computer Vision with Applications for Wildlife Conservation”.

Seth Juarez holds a Master’s Degree in Computer Science where his field of research was Artificial Intelligence, specifically in the realm of Machine Learning. Seth is a Microsoft Evangelist working with the Channel 9 team. When he is not working in that area, Seth devotes his time to an open source Machine Learning Library, specifically for .NET, intended to simplify the use of popular machine learning models, as well as complex statistics and linear algebra.

Deep Learning is one of the buzziest of tech buzz words at the moment. This session is designed to remove the mysticism from this amazing form of Artificial Intelligence. Attendees will be led through the wilderness of the foundational principles underlying modern machine learning until they reach the oasis of a full-fledged understanding of deep learning for computer vision. While this session is not for the faint of heart, initiates will attain a solid understanding of the basics of machine learning all the way through powerful image-deciphering convolutional neural networks.

Come check out Seth Jaurez’s talk at ML4ALL happening April 28th-30th in amazing Portland, Oregon! Get your tickets to attend here. For the schedule, our excellent sponsors docs for the conference, check out the ML4ALL Conference Site!

Erika Pelaez Presenting “Building a Machine Learning Classifier to Listen to Killer Whales”

UPDATED: Video Added from the Conference!

Introducing Erika Pelaez > @midoridancer < presenting “Building a Machine Learning Classifier to Listen to Killer Whales“.

erika-pelaezData Scientist with experience and love for Machine Learning. I like making smart things and have worked with a diverse types of data from biological to transportation.

Did you know that Machine Learning can help protect killer whales? Orcasound (https://github.com/orcasound) is a magnificent open source project for people to connect to their neighbor killer whales of the pacific northwest. They provide a platform that continuously broadcasts the underwater sounds from the Puget Sound area to anyone willing to listen. Come to my talk and I’ll show you how we’re applying Machine Learning with the Scikit-learn Python library against web scraped audio to build models that can be used for signal collection and classification.

Avid users spend time listening to mostly noise or ships but frankly the majority is there just to hear the orca sounds. The present talk will narrate the process we are following to automatically detect and classify orca vs non orca (false killer whale and humpback whale) sounds.

The first challenge faced with this project was getting labeled data as the raw transmissions are unlabeled so my first approach was to build a dataset from scratch by web scraping audio from the internet using Beautiful soup then I used a bash script for making sure all the files had a maximum duration of 5s as this is the duration of the files that orcasound saves. The feature extraction of the audio files was handled with the librosa library from Python. I finally built a Random Forest Classifier with the scikit-learn Python library that was able to reach an accuracy of 99 +/-2% with a 10 fold cross validation. The next steps will be to have the model accessible through an API and send the collected signals to it for classification, after a signal is detected a notification could be send to the users so they don’t have to listen to all the noise.

Come check out Erika Pelaez’s talk at ML4ALL happening April 28th-30th in amazing Portland, Oregon! Get your tickets to attend here. For the schedule, our excellent sponsors docs for the conference, check out the ML4ALL Conference Site!

Creating Distributed Database Application Starter Kits

I’ve boarded a bus, and as always, when I board a bus I almost always code. Unless of course there are people I’m hanging out with then I chit chat, but right now this is the 212 and I don’t know anybody on this chariot anyway. So into the code I go.

I’ve been re-reviewing the Docker and related collateral we offer at DataStax. In that review it seems like it would be worth having some starter kit applications along with these “default” Docker options. This post I’ve created to provide the first language & tech stack of several starter kits I’m going to create.

Starter Kit – The Todo List Template

This first set of starter kits will be based upon a todo list application. It’s really simple, minimal in features, and offers a complete top to bottom implementation of a service, and an application on top of that service all built on Apache Cassandra. In some places, and I’ll clearly mark these places, I might add a few DataStax Enterprise features around search, analytics, or graph.

The Todo List

Features: The following detail the features, from the users perspective, that this application will provide. Each implementation will provide all of these features.

  • A user wants to create a user account to create todo lists with.
  • A user wants to be able to store a username, full name, email, and some simple notes with their account.
  • A user wants to be able to create a todo list that is identified by a user defined name. (i.e. “Grocery List”, “Guitar List”, or “Stuff to do List”)
  • A user want to be able to logout and return, then retrieve a list from a list of their lists.
  • A user wants to be able to delete a todo list.
  • A user wants to be able to update a todo list name.
  • A user wants to be able to add items to a todo list.
  • A user wants to be able to update items in the todo list.
  • A user wants to be able to delete items in a todo list.

Architecture: The following is the architecture of the todo list starter kit application.

  • Database: Apache Cassandra.
  • Service: A small service to manage the data tier of the application.
  • User Interface: A web interface using React/Vuejs ??

As you can see, some of the items are incomplete, but I’ll decide on them soon. My next review is to check out what I really want to use for the user interface, and also to get a user account system figured out. I don’t really want to create the entire user interface, but instead would like to use something like Auth0 or Okta.

May I Ask?

There are numerous things I’d love help with. Are there any user stories you think are missing? Should I add something? What would make these helpful to you? Leave a comment, or tweet at me @Adron. I’d be happy to get some feedback and other’s thoughts on the matter so that I can ensure that these are simple, to the point, usable, and helpful to people. Cheers!

Lena presents “So You Want to Run Data-Intensive Systems on Kubernetes”

If you’re interested in running data-intensive systems (think Apache Cassandra, DataStax Enterprise, Kafka, Spark, Tensorflow, Elasticsearch, Redis, etc) in Kubernetes this is a great talk. @Lenadroid covers what options are available in Kubernetes, how architectural features around pods, jobs, stateful sets, and replica sets work together to provide distributed systems capabilities. Other features she continues and delves into include custom resource definitions (CRDs), operators, and HELM Charts, which include future and peripheral feature capabilities that can help you host various complex distributed systems. I’ve included references below the video here, enjoy.

References:

‘bash’ A.K.A. The Solution for Everything – Bourne Shell as per v7 Unix to Today’s

In 1979 Unix v7 started being distributed with the original Bourne Shell. Simply, it’s a program that sits at /bin/sh and runs in the terminal. You may ask, “what’s the difference between a shell and the terminal?” Let’s cover that right now, because it’s something that routinely isn’t common knowledge, but it really ought to be as it sets the basis for understanding a lot of what is going on in Unix based systems (that includes almost every practical system on a PC, Server, in the cloud, on your phones, and more. Probably easiest to explain it simply as everything that isn’t the Microsoft Windows OS)

A Shell and the Terminal

Terminal – A terminal is the text input and output environment on the system.

Shell – This is the command line interpreter that is run at the terminal.

Another point of context, is that a terminal, shell, and the word console are all used in various ways and sometimes interchangeably. However, these words do not mean the same thing at all. They are distinct individual parts of the system. For example, console, which is used in a strangely disingenuous way all over Microsoft phrasing, is the physical terminal of the system, which is where the system terminal, i.e. the thing I’ve described above, actually runs in so that we can type and interface with it as humans.

Albeit, as English does, these definitions aren’t always taken as the exact, appropriate, and pedantically correct definitions today. For example, many at Microsoft argue that the console is just the terminal, that the terminal is the console. Sure, ok, that’s fine I can still follow along in the conversation, and this adds context, for when someone steps out of line and uses the more historically specific definition in context of a conversation.

Alright, that’s all groovy, so now we can get back to just talking about the shell, all the power it gives the Unix/Linux/POSIX System user, and touch on the terminal or console as we need to with full context of what these things actually are!

Gnu-bash-logo.svgIntroducing Bash!

Alright, with that little bit of context around Bourne Shell, let’s talk about what we’ve actually got today running as our shell in our terminal on our console on the computers we work with! The Bourne Shell, years later had a replacement written for it by Brian Fox. He released it in 1989 and over the years it became a kind of defacto replacement of Bourne Shell. The term ‘BASH’ stands for Bourne Again SHell.

440px-Bash_screenshotThe Bash command syntax is a superset of the Bourne Shell syntax. It provides a wide range of commands that includes ideas drawn from the Korn shell (ksh) and the C shell (csh) such as command line editing, command history, the directory stack, the $RANDOM and $PPID variables, and POSIX command substitution syntax. If many of those things make you think, “WTF are these variables and such?” have no worries, I’ll get to em’ soon enough in this series!

But with that, this is the beginning of many short entries on tips, tricks, tutorials, syntax, history, and context of bash so until next time, cheers!

References & Collected Materials