The Division of Mathematics and Natural Sciences at Reed College invites you to a public lecture by Prof. Harry L. Swinney, Sid Richardson Foundation Regents Chair of Physics and Director of the Center for Nonlinear Dynamics at the University of Texas at Austin. Prof. Swinney is one of the pioneering figures in the study of chaos theory and his lab has played a leading role in the study of nonlinear dynamics over the past 40 years. He is a member of the National Academy of Sciences and his work has been recognized with numerous awards, including the Moser Prize, the Richardson Medal, and the Boltzmann Medal.

From spatial patterns like the stripes on a zebra to temporal patterns like the rhythmic beating of the heart, patterns are ubiquitous in nature. Understanding how these patterns emerge is one of science’s most enduring mysteries. In this lecture, aimed at a general audience, Prof. Swinney will discuss how ordered patterns emerge as systems are driven away from thermodynamic equilibrium. While no general theory of pattern formation currently exists, new analysis techniques, experiments, and computational methods can provide general insights into pattern formation in a diversity of physical, chemical, and biological systems.

Spontaneous pattern formation in bacterial colonies

Sponsored by the Office of the Dean of the Faculty at Reed College.

This is the first month of our new format, based on discussion following the survey: The first half will be geared toward beginners, and the second half will be geared toward more advanced material.

For the next several months the beginner material will be a series of lessons in the Haskell programming language. We will be following Brent Yorgey's CIS 194 syllabus (http://www.seas.upenn.edu/~cis194/spring13/lectures.html). So bring a laptop, or just follow along. Between months you are encouraged to work on the assignments and we will review them. Lyle will be leading the lecture this month.

This month's advanced talk will be delivered by Leif, who will be following up his discussion of data parallelism in Spark (Scala) and Haskell.

This month, Echo will be leading us through Haskell Lesson 2 (Week 2 at http://www.seas.upenn.edu/~cis194/spring13/lectures.html)! The category theory talk has been rescheduled for April.

This meeting continues our Haskell lesson series with Echo delivering Lesson 3 on Recursion Patterns, Polymorphism, and the Prelude from Brent Yorgey's CIS194 course (http://www.seas.upenn.edu/~cis194/spring13/lectures.html).

Lyle will give an introduction to category theory, a theory about mathematical structures and their relationships, which has applications in functional programming.

The meeting will be at Collective Agency in the Tiffany Center - the same place as the February meeting. The elevator is expected to be restored to operation by then. (UPDATE: Elevator service to the 8th floor has not yet been restored, so you will have to walk from the 4th floor.) Someone will wait in the lobby to let you in as the front doors are locked after 6. The meeting is on the 8th floor.

This week is going to be Great! We'll have our first interactive session. Ernest Bonat will share his idea this week on "Tensorflow or TFLearn?"

Join us for another fun-filled evening of learning and discussion!

Tonight, Lyle will present Lesson 5 from Brent Yorgey's CIS 194 lectures: http://www.seas.upenn.edu/~cis194/spring13/lectures/05-type-classes.html, as well as reviewing the homework from Lesson 4.

Then, Matt Rice will talk about the 1ML language, a variant of ML which unifies the main expression/type language with the language of the module system (signatures, structures and functors). He's also been creating his own language derived from it.

Do you want to start using Kaggle? Why not learn as a group? I'll share the basics and an example how to start the competition "Titanic - Machine Learning from Disaster".

The second half of our session, we'll experiment with our open idea session. The winner will be awarded Innovator of the week. The winner has the highest potential to be added to our next session.

Here is the link to my transcript and video links. Enjoy! https://portlanddatascience.wixsite.com/home/single-post/2017/06/19/Kaggle-Session

We had many volunteers to talk about Python. We'll share the basics, Logistic Regression, and how to solve the Kaggle Titanic competition.

We'll have a few lightning talks then an open session for new topics.

You are welcome to join us and share your knowledge!

This month, Leif will present Lesson 6 on Lazy Evaluation from Brent Yorgey's CIS 194 lectures.

Then, Rob Norris will talk about free things.

Meeting is on the 8th floor of the Tiffany Center. If you arrive before the meeting starts, there will be someone in the lobby to open the front door for you. If not, there will be a sign posted with a phone number for you to call, and someone will come down to let you in. Take the elevator on the right to the 8th floor, and exit to your right. The sign next to the space says Forge Portland. We meet in the large open area there. 

Do you want to learn Python Pandas and Machine Learning? Check out our group. We're just getting started with the Titanic competition. Find out you can solve a real world Kaggle problem with Python and Machine Learning.

At the end of the session, we'll brainstorm a new hot topic for the following week presentation. The winning idea will get the innovator of the week.

Join the fun!

All aboard the Titanic. Your task, if you choose to accept it, pick a character on the Titanic. Then, you must build a machine algorithm to predict if you survived.

Now that you are afraid of dying, what's the best way to predict your survivorship?

Python Pandas and Numpy. If you want to learn how to build a machine learning algorithm check us out next Saturday at 1 pm in the Hillsboro Brookwood Library. We be using the Kaggle dataset to build our code.

Do you want to learn Python and Machine Learning? Check out our group. We're getting started with the Titanic competition. Find out you can solve a real world Kaggle Titanic problem with Python and Machine Learning.

At the end of the session, we'll brainstorm a new hot topic for the following week presentation. The winning idea will get the innovator of the week.

Join the fun!

Here's our agenda

We've located at the Hillsboro Public Library. We'll be meeting in Conference room A, on the second floor.

We had several new college students join us last week. We had a new idea to help college students with open data. Bring your college problems and we can help brainstorm how to help.

Did you know the top skill people want to learn is a language? How about a programming language like Python? Python is very powerful in Machine Learning. Check out our group on Saturday's at 1 PM.

We're working together to solve the Kaggle Titanic competition. Find out how you can learn Python and Machine Learning very easily and quickly.

At the end of the session, you'll get an opportunity to brainstorm and present new topic ideas for the following week. Did you know you learn exponentially more when you prepare a topic vs attending as a learner? The winning idea will get the innovator of the week.

Join the fun!

This month, we'll be meeting in a new location! Collective Agency has moved to 511 SW 10th Ave. We'll be meeting in the main area.

First, we'll cover Lesson 7 on Folds and Monoids from Brent Yorgey's CIS 194 Haskell lectures.

Then, Jamon Holmgren will explain his implementation of the A pathfinding algorithm in Elm. A is used in games to calculate the least-cost path for a computer character to move from one spot to another. Elm is a language similar to Haskell (but simpler) that compiles down to JavaScript, used for apps that run in web browsers.

Did you know the top skill people want to learn is a language? How about a programming language like Python? Python is very powerful in Machine Learning. Check out our group on Saturday's at 1 PM.

We're working together to solve the Kaggle Titanic competition. Find out how you can learn Python and Machine Learning very easily and quickly.

At the end of the session, you'll get an opportunity to brainstorm and present new topic ideas for the following week. Did you know you learn exponentially more when you prepare a topic vs attending as a learner? The winning idea will get the innovator of the week.

Join the fun!

We have had a wonderful turnout of college students. It would be great to help with your projects. Please bring stop by and check us out.

Did you know the top skill people want to learn is a language? How about a programming language like Python? Python is very powerful in Machine Learning. Check out our group on Saturday's at 1 PM.

We're working together to solve the Kaggle Titanic competition. Find out how you can learn Python and Machine Learning very easily and quickly.

At the end of the session, you'll get an opportunity to brainstorm and present new topic ideas for the following week. Did you know you learn exponentially more when you prepare a topic vs attending as a learner? The winning idea will get the innovator of the week.

Join the fun!

Data Scientists,

Do you want to learn Python the Machine Learning Language?

or

Did you know MongoDB is the most popular NoSQL database? How interesting would it be if you could see it on a Raspberry Pi?

or

How about the schema of Stack Exchange the extremely useful site for stack overflow? Here is a link to Matt's presentation.

We have three excellent presentations this week. At the end of the session, we'll brainstorm a new interesting topic for the following week presentation. The winning idea will get the innovator of the week.

Presenter Topic Time Everyone Introductions 1:00 - 1:10 PM Matt SQL Project 1:10 - 1:35 PM Michael Raspberry Pi & Mongo 1:35 - 2:00 PM Garrett Python 2:00 - 2:20 PM Everyone Brainstorm & Vote Topics 2:20 - 2:30 PM

Do you want to learn Python the Machine Learning Language?

Do you want to see a live demo of an Arduino robot?

How about the Stack Exchange Schema?

We're exploring all of these innovative areas all in one session. We'll share a ton of knowledge in a short amount of time. Don't miss it!

At the end of the session, you'll get an opportunity to brainstorm and present new topic ideas for the following week. Did you know you learn exponentially more when you prepare a topic vs attending as a learner? The winning idea will get the innovator of the week.

Here's a link to my previous Python session https://youtu.be/OX2fVsKbwXg

Here's a link to our topic agenda https://docs.google.com/spreadsheets/d/15cmTfCJdwttpYEONdY-uGxMbCo7Z8_sWCKznKknGZ4k/edit?usp=sharing

Join the fun!

Lyle will present Brent Yorgey's CIS 194 Lesson 8 on IO in Haskell.

Then Lyle will present Vintage BASIC, a BASIC interpreter he wrote in Haskell some years ago but has recently revised.

Data Scientists,

Do you want to learn about an unmanned robotic spacecraft Cassini?

How about programming a game in Python?

What about the data scheme behind Stack Overflow?

We have three amazing topics with code to share with the group. At the end of the session, we'll brainstorm next topics and someone will be awarded innovator of the week

Here's a YouTube of the previous session on Pygame. https://youtu.be/tRCYaCWzRnU

Join the fun!

Do you want to learn more about API calls to Google and Better Doctor?

How about Juno-Jupiter?

At the end of the session, we'll brainstorm new ideas and the winner will be crowned innovator of the week!

Here's a YouTube of the session from the previous week. https://youtu.be/U5sdLYHeJgk

Join the fun!

Agenda Presenter Topic Time Everyone Introductions 1:00 - 1:10 PM Kimberely API calls - Google Maps, Better Doctor 1:10 - 1:25 PM Everyone API calls - Q&A 1:25 - 1:30 PM Kateyln Juno-Jupiter 1:30 - 1:45 PM Everyone Juno-Jupiter Q&A 1:45 - 1:50 PM Everyone Brainstorm & Vote Topics 1:50 - 2:00 PM

Data Scientists,

Do you want to learn more about Data Visualization, BI, and Data Lakes?

How about more on Python Pandas and Data Frames? I'll be giving some examples of housing pricing trends.

At the end of the session, we'll brainstorm a new interesting topic for the following week presentation. The winning idea will get the innovator of the week.

Here's a YouTube of the session from the previous week. https://youtu.be/U5sdLYHeJgk

Join the fun!

Agenda Presenter Topic Time Everyone Introductions 1:00 - 1:10 PM Justin Data Visualization,BI,Data Lakes 1:10 - 1:25 PM Everyone Q&A 1:25 - 1:30 PM Garrett Python 1:30 - 1:45 PM Everyone Q&A 1:45 - 1:50 PM Everyone Brainstorm & Vote Topics 1:50 - 2:00 PM

Echo will present Brent Yorgey's CIS 194 Lesson 9 on functors in Haskell.

Brian Ginsburg will give a short presentation on Minima (https://brianginsburg.com/minima/), a playground for experimenting with minimalist musical patterns, which he wrote in Elm.

We will have extra time in this meeting for hands-on learning. You are encouraged to bring a laptop or work together with someone else. You can practice working with functors, hack on Minima, or ask any other questions you might have.

Come celebrate the 10th anniversary of PDX Func! The first meeting was on 11/15/07. There'll be food and drink and cake! We'll also discuss the new format for meetings based on the survey results. We will also go over the Applicative Functor lesson from CIS 193, which will be our final lesson from that track.

Dear Learners,

Do you enjoy learning and sharing knowledge to help people solve problems? This week we're going to share about patents.

We'll have a thirty-minute talk and at the end of our session, we'll brainstorm and vote for a new interesting topic for ideas on upcoming presentations. The winning idea will get the innovator of the week.

Join the fun!

Do you want to learn about Machine Learning for IoT devices? Chris is planning to join us fSensiML http://www.sensiml.com/

Do you enjoy learning and sharing knowledge to help people solve problems? Check out this video (https://www.youtube.com/watch?v=u6XAPnuFjJc) to see what we're about.

We'll have a short presentation and at the end of our session, we'll brainstorm and vote for a new interesting topic for the following week presentation. The winning idea will get the innovator of the week.

Join the fun!

Do you enjoy learning and sharing knowledge to help people solve problems? Check out this video (https://www.youtube.com/watch?v=u6XAPnuFjJc) to see what we're about.

We'll have a 30-minute demo and at the end of our session, we'll brainstorm and vote on new interesting topic ideas for upcoming presentations. The winning idea will get the innovator of the week.

Join the fun!

The study of quantum computation has been motivated, in part, by the possibility that quantum computers can perform certain tasks dramatically faster than classical computers. Many of the known quantum-over-classical speedups, such as Shor’s algorithm for factoring integers and Grover’s search algorithm, can be framed as oracle problems or concept learning problems. In one model of concept learning, a student wishes to learn a concept from a teacher by making queries of the teacher. In the interest of efficiency, the student wishes to learn the concept by making as few queries as possible. For any such concept learning problem, there is a corresponding quantum concept learning problem. In the quantum version, the student is allowed to ask a superposition of queries – mathematically, a linear combination of queries – and the teacher answers with the corresponding superposition of the responses. After making this idea precise, we will examine several concept learning problems and their quantum analogues. We will discuss recent joint work with Daniel Copeland (UCSD), in which we show how tools from representation theory can be used to precisely analyze any quantum learning problem with sufficient symmetry.

Will also be streamed live on the Galois YouTube channel: https://www.youtube.com/channel/UC1TJ20iM_dCa0pq6h0tA79w