- It’s ALIVE! Methods to deploy your next website!
I know when I started doing web development, there were tons of tutorials for how to build a website but a lack of methods for how to bring it…to life! Once I have some code running on my computer how does that transform into a living website available to the world?!
I’ve since learned that there are many methods, especially since the dawn of cloud computing. Platform as a service or infrastructure as a service has made it easier and more reliable to deploy code.
To demystify these different methods, Matt Kingsbury will be presenting on deploying a Django website live to the web. Matt is a leading consultant in the SLC Silicon Slopes. He’s worked on many web and data based projects for businesses and city across the country. We’re excited to have his expertise to learn more about bringing a website…to life!!!
- Build vs Buy: If I Build there will be trouble! If I Buy it will be double!
Should I build or should I buy now?! If I Build there will be trouble! If I Buy it will be double! So come on and let me know! haha https://www.youtube.com/watch?v=BN1WwnEDWAM
The decisions about tech stacks have some of the longest term impacts. They can cost or save millions of dollars depending on the choices you make today. In the growing world of managed services, the decision of paying for a piece of infrastructure has never been more accessible. But with every managed solution there are costs and limitations. How do you decided when to go with a managed service? How do you evaluated the choices? How to you validate vendors? How do you negotiate prices and resources?
Ayla Khan is a top software engineer at Recursion Pharmaceuticals working to maintain their state of the art machine learning pipeline and infrastructure. At this meetup, she's going to help us understand the considerations needed for Build vs Buy, share her experiences, and help us think about how we can make the right decision for our technology use case.
Looking forward to seeing you there!
- Python of the Future! Looking at the best features of Python!
Draft of our agenda:
For our beginner talk, we'll be showing how to teach and learn python in 2021. Remember that when you teach, you learn twice!
Our more advanced discussion will be some live experimentation with Python 3.10's pattern matching: https://www.python.org/dev/peps/pep-0634/
- SLCPy 7th Anniversary Soiree!!!
Hi SLCPy Pythonistas!
It's time for our...wait for it... 7TH ANNIVERSARY!!! In lieu of our normal in person dinner, we've organized a [gather.town](https://gather.town/) soiree!
Please join us if you never have or come all the time! Bring friends! It's a Party :D Social event to get to know others and have a social relief from pandemic isolation. Looking forward to seeing you there! Please RSVP :)
6:00pm - 6:30pm: mingle
6:30pm - 6:40pm: announcements
6:40pm - 7:00pm: group game
7:00pm - PARTY ALL NIGHT!: Games and mingling :)
Also, Dylan will be presenting results from the first ever SLCPy Survey. If you haven't filled it out yet, there are still a few more days to do so. https://forms.gle/GkbWqYhoxBiBfXCq8 takes < 5 minutes. Thanks!
- Your next data science project is likely to fail, with Tyler Folkman (B.E.N)
According to Gartner, over 85% of data science projects fail. A report from Dimensional Research indicated that only 4% of companies have succeeded in deploying ML models to production environment. In this talk, I will discuss why I think this happens and what skills you can develop to make sure this doesn't happen at your company.
Tyler is the Head of AI at BEN. At BEN, Tyler leads a team that strives to reinvent product placement with machine learning. Before BEN, Tyler worked at Ancestry and helped create machine learning algorithms to connect millions of family trees. Tyler has a Master's in Computer Science from the University of Texas at Austin.
- Monitoring Machine Learning Models, with Danny Leybzon (Imply.io)
What happens after you deploy a machine learning model? How do you make sure that your model's performance doesn't degrade as data and the world change? In this talk, Danny D. Leybzon will explain how monitoring ML models in production is key to deriving value from your machine learning initiatives.
The talk is meant to answer three main questions: 1. "What is ML monitoring?" 2. "Why do we care about ML monitoring?" 3. "How do we monitor ML models?" It seamlessly intertwines both theory and practice, leaving viewers with an in-depth understanding of how to think about their machine learning models in production
Danny D. Leybzon has worn many hats, all of them related to data. He studied computational statistics at UCLA, before becoming first an analyst and then a product manager at a big data platform named Qubole. Since then, he has worked to evangelize machine learning best practices, talking on subjects such as distributed deep learning, productionizing machine learning models, and automated machine learning.
When Danny's not researching, practicing, or talking about data science, he's usually doing one of his numerous outside hobbies: rock climbing, backcountry backpacking, skiing, etc.
- The Python Crystal Ball: Using Machine Learning to Predict...THE FUTURE!
Humans often want to know what the future will bring. Who will win the election? When will a pandemic end? Which choice of socks will optimize my individual happiness by next year? And while the future is never certain (e.g. 2020) we often learn from the past to predict what will happen in the future. And today, we have amazing technology and mathematics humans have developed to help us encode this more than ever before!
Dylan Gregersen will be presenting methodologies and Python code for doing time series forecasting. (He promised Faris and Joe not to do any covid related forecasting so don’t worry, he’ll not be touching that one). He’ll be going over a methodology for time series forecasting, several typical machine learning models, and how to take this code to production.
The crystal ball predicts...you will enjoy attending!
- Optimization models in decision support systems, with Adi Nagarajan
Optimization models have been widely used since the 1940s for solving a wide array of business, engineering and social science problems. Over the last ten years at Extra Space we have extensively used these techniques to drive business value. We have used them in our revenue management systems, churn reduction programs and improved our efficiencies in spending marketing dollars.
All of our advanced analytical systems have two primary components, a forecasting or predictive component and an optimization component. The optimization component allows us to maximize revenue, to minimize churn, etc.
In this talk, I will given an overview of the different optimization models and walk through the optimization features in our advanced analytical systems.
About the Speaker
Adi Nagarajan is a Sr. Data Scientist with a Masters Degree in Industrial Engineering. He has been with Extra Space Storage for the past 7 years, having experience working on their revenue management and marketing optimization systems.
- Remote Meetup: Playing with GPT-3 guided by Bob Bodily
A playful introduction and Demo of OpenAI's new GPT-3 Language Model
OpenAI recently released their new language model in private beta through an API. I have beta access and we will be doing a demo of the online playground in this talk. If you haven’t seen GPT-3 in action, you can search GPT-3 on Twitter to get a sense for what people have been able to do with it. The natural language abilities of GPT-3 are much better than GPT-2 (former version of OpenAI’s language model) and we’ll check out some of its strengths in this talk, including chat, Q&A, translation, and text generation. Bob Bodily will be guiding us through a demo of GPT-3 in addition to answering your questions on-stream.
Bob Bodily received a PhD in instructional technology at Brigham Young University and is a Senior Data Scientist at Lumen Learning, an educational technology startup based in Portland, OR.
There will be (remote) raffle prizes and a beginning python talk during our online meetup. In addition, our members are more than welcome to socialize after the main meetup has concluded.
We will be recording the main talk and Zoom call for our YouTube channel. Please mute your video and microphone if you don't want to participate in a public video.