2018-Nov-10
Start :
8:00
Stop :
9:00
Breakfast & Registration
2018-Nov-10
Start :
9:00
Stop :
9:30
Opening Remarks
2018-Nov-10
Start :
9:30
Stop :
10:30
Ballroom (2nd Floor)
Solmaz is the VP of Data Science and Engineering at Shopify leading the data organization. Her teams build the data platform and the machine learning solutions that power Shopify's internal and merchant facing data products including Shopify's real-time Order Fraud Analysis, Shopify Capital and Shopify Home. Her and her teams build majority of their data solutions using Python (and Spark) and she is a big fan of the Python community. With multiple graduate degrees in computer science and machine learning, prior to joining Shopify, she worked at Morgan Stanley as an analyst and at McGill university as a cancer researcher, applying machine learning techniques to predict breast cancer outcome. Solmaz has a passion for building high quality data products that delight users and solve real world problems.
2018-Nov-10
Start :
10:30
Stop :
11:00
Ballroom (2nd Floor)
Harry Potter is an incredibly popular franchise that shaped a generation, but it's also been critiqued for its biased portrayal of female characters. Does that claim hold up to a quantitative analysis? In this talk we'll use Python and Natural Language Processing techniques to find out.
Terrace (3rd floor)
Today, Big Data is becoming an important component of IT in large organizations. The talk presents three methods to aggregate big data using Python dictionaries and the API of Apache Spark known as PySpark. The talk tries to simplify complex methods and presents them in a simple approach.
St. Patrick (3rd floor)
At Wave, I've been a part of the team, from inception to now, rewriting and replacing the old accounting system. I want to talk about the challenges migrating a system with over 2 million sign ups with no downtime. The systems are radically different making it challenging at time. We're 60% done.
St. David (3rd floor)
Apache Spark is a fast and general engine for big data processing. Using PySpark, you can work with Spark DataFrames in Python. The target audience is familiar with Python and looking to get their feet wet with data science and/or the Spark framework. This tutorial will cover reading in data from files and basic DataFrame operations. While this session cannot provide enough background to support professional work with Spark, we aim to provide some interesting initial tools and pointers on how to go deeper for those interested.
2018-Nov-10
Start :
11:10
Stop :
11:40
Ballroom (2nd Floor)
On July 12, 2018, Guido van Rossum gave himself 'a permanent vacation from being BDFL' with no guidance on how to proceed. This talk will discuss how the Python development team has tried to handle situation and where things currently stand.
Terrace (3rd floor)
A shopping list is an integral part of the shopping experience for many consumers. Several mobile retail studies indicate that potential customers place the highest priority on features that help them create and manage personalized shopping lists. We propose one solution written in PYTHON.
St. Patrick (3rd floor)
Python has made the jump to embedded software running on microcontroller hardware. This talk will introduce CircuitPython: a fork of MicroPython (a implementation of Python 3 designed to run on small hardware) that takes it to exciting new hardware and makes it very beginner/learner friendly.
2018-Nov-10
Start :
11:50
Stop :
12:20
Ballroom (2nd Floor)
Jason took a short leave of absence to help the Canadian federal government adopt modern software development practices. In this talk he’ll talk about his reasons for pursuing this opportunity, whether he’d recommend it to others, and lessons learned along the way.
Terrace (3rd floor)
Mozilla ships a new version of Firefox every 6-8 weeks, new Betas are released twice a week, and Nightly builds are released twice a day. Learn how Python is used at Mozilla in all stages of the build and release pipeline to bring Firefox to the world!
St. Patrick (3rd floor)
What do you think of when you hear “artificial intelligence”? Perhaps self-driving cars, autonomous robots and Siri, Alexa or Google Home? But it doesn’t have to be that complex. You can build a powerful image classification model within a topic that inspires and interests you - with 3 easy steps.
2018-Nov-10
Start :
12:20
Stop :
13:30
Lunch
2018-Nov-10
Start :
13:30
Stop :
13:40
Ballroom (2nd Floor)
Teaching computational thinking in the classroom is a challenge as there's a wide range of skills, including the teacher's. The Gigglebot is a microbit rover that covers the steps from no coding to Python coding through a variety of approaches so that no one in the classroom gets left behind.
Terrace (3rd floor)
Software development requires us to solve difficult, urgent problems with other smart people. Working with other people is hard, and we often leave our best ideas on the floor. In this talk, we’ll learn principles and techniques to be inclusively and effectively creative together.
St. Patrick (3rd floor)
So you've got an idea for a machine learning product, but how do you actually get it to production? From going on-call for ML models, to ensuring that models built by your data scientists can be used by your engineers, join me for a fast paced guide to the world of data science in production.
St. David (3rd floor)
Learn the ABCs of Kubernetes and how to get started on using managed containers for your python development on your local machine and also for production deployments on a cloud provider-managed Kubernetes cluster.
2018-Nov-10
Start :
13:45
Stop :
13:55
Ballroom (2nd Floor)
How does one make use of that raspberry pi they bought years ago? This talk will summarize how you can turn your raspberry pi into a home security system, utilizing slack as a notifications and control system.
Terrace (3rd floor)
This talk presents the use of Python in environmental (energy) scenario research. We analyze different energy scenarios and apply community detection (Louvain method) to reveal the core issues that could support Canada’s energy transition in the future, which policymakers might find them insightful.
St. Patrick (3rd floor)
A/B testing is a valuable and in-demand skills that data analysts, BI developers, and data scientists have in their analytical toolkits. This beginner-oriented talk will explain the basic intuitions and statistical theory behind A/B testing and showcase a simple implementation in Python.
St. David (3rd floor)
2018-Nov-10
Start :
14:00
Stop :
14:10
Ballroom (2nd Floor)
Python is showing an incredible growth in many fields, including academia. By enumerating the challenges we face in sustainable research software development and how Python's unique strengths are catering to them, I hope to explain this growth and encourage further adoption for scientific computing!
Terrace (3rd floor)
The short story of how we used OAuth and JWTs (JSON Web Tokens) to add identity and authentication in every call to one of our widely used services. Includes an overview of how JWTs work and different OAuth flows for every use case.
St. Patrick (3rd floor)
Paid internet trolls linked to the Russian government tried to influence the U.S. election with divisive social media posts. But they also targeted Canadians, at a smaller scale. Here's how I used Python to find tweets aimed at dividing Canadians among a trove of 3 million troll tweets.
St. David (3rd floor)
2018-Nov-10
Start :
14:15
Stop :
14:45
Ballroom (2nd Floor)
In this talk, we'll learn about a highly controversial proposed change to Python syntax, the rationale for it, and the fallout as the result of it.
Terrace (3rd floor)
Defeat your enemies, save the environment, and win your fantasy league!
St. Patrick (3rd floor)
Diversification is a portfolio construction and risk management technique used in finance that aims to minimize the impact of any single investment’s performance on that of the total portfolio. How can Python be used to measure diversification in a quantitative fashion?
St. David (3rd floor)
If you have an evolving domain and process owners of varying expertise, then Domain Driven Design is a great approach. In this tutorial I would explain the concepts of DDD, and interactively introduce a Django project with a 'drawing board to on board' experience from mindset to implementation.
2018-Nov-10
Start :
14:55
Stop :
15:25
Ballroom (2nd Floor)
WSGI is the foundation of most Python web frameworks, but there's a good chance you've never had to interact with it directly. In this talk we'll explore why it exists, how it works, and what the heck it's doing in your stack.
Terrace (3rd floor)
When python interacts with strongly-typed systems a mapping is implicitly created. Every. Single. Time. The (1 to 0, 1 to 1, 1 to many) relationships can be unwieldy. A related stack overflow question, Wes McKinney replies 'Welcome to Hell'. This is the story of an attempt to innovate out of hell.
St. Patrick (3rd floor)
Learn how to build a network web in Python to reflect conversations between people based on Slack conversations. Then, build a natural language processing model to evaluate what all those people are talking about, and which conversations determine who in the network carries 'technical knowledge'.
St. David (3rd floor)
2018-Nov-10
Start :
15:25
Stop :
15:45
Break
2018-Nov-10
Start :
15:45
Stop :
16:15
Ballroom (2nd Floor)
Want to know how Spotify, Amazon, and Netflix generate recommendations for their users? This talk walks through the steps involved in building a recommendation pipeline, from data cleaning, hyperparameter tuning, model training and evaluation.
Terrace (3rd floor)
Even though Flask is a 'micro' framework, it's doing quite a lot between receiving a request and returning a response. Learn about the lifecycle of a Flask request and how you can get in the middle of it to make your app more powerful.
St. Patrick (3rd floor)
Software design is a tricky to get right, even for experienced developers. There is simply too much choice and too much information to consider. How do we slow the incidental complexity of our systems with every new feature we add? Learn how simpler patterns and more constraints can actually lead to more reliable results.
St. David (3rd floor)
Search engine optimization (SEO) requires a variety of technical considerations, such as page titles, redirects and structured data. With Python we can build a scalable pipeline to extract and audit this data from web pages. We’ll show how this (and more) can be done using a Jupyter Notebook!
2018-Nov-10
Start :
16:25
Stop :
16:55
Ballroom (2nd Floor)
Visual Studio Code is the most popular tool used by developers in Stack Overflow's 2018 developer survey, and is quickly growing in popularity among Python developers. In this talk we'll show how to get productive and take full advantage of VS Code has to offer Python developers.
Terrace (3rd floor)
Library maintainers, how can you innovate without breaking projects that depend on you? Follow semantic versioning, add APIs conservatively, add parameters compatibly, write an upgrade guide, use DeprecationWarnings, and publish a deprecation policy. Break backwards compatibility rarely and wisely.
St. Patrick (3rd floor)
Creating a custom database by mining five ticket sellers allowed us to expose staggered rollouts, experiments with variable pricing and reveal how high-demand events actually sell. From accessing Ticketmaster’s databases to mining the data, we’ll walk through CBC’s ticket scalping investigation.
St. David (3rd floor)
2018-Nov-10
Start :
17:00
Stop :
18:00
Ballroom (2nd Floor)
Graham is the VP of Applied Sciences and Research at Wave, where he’s responsible for the integration of new technologies and research areas into the company, primarily Machine Learning and Artificial Intelligence. Over the years, Graham has built, led and managed teams from 5 to 100 as a founder, manager, executive and board member. He has a passion for solving complex problems by creating fun, inclusive, high performing teams. In previous lives, he’s built multi-petabyte systems, found homes for lost cats and puppies, done stand up comedy at weddings and night clubs (including an unfortunately momentous poetry jam) and taken himself far too seriously.