About Me
Before working in Developer Relations, Cheuk has been a Data Scientist in various companies which demands high numerical and programmatical skills, especially in Python. To follow her passion for the tech community, Cheuk is now the Developer Advocate at Anaconda. Cheuk also contributes to multiple Open Source libraries like Hypothesis and Pandas.
Besides her work, Cheuk enjoys talking about Python on personal streaming platforms and podcasts. Cheuk has also been a speaker at Universities and various conferences. Besides speaking at conferences, Cheuk also organises events for developers. Conferences that Cheuk has organized include EuroPython (which she is a board member), PyData Global and Pyjamas Conf. Believing in Tech Diversity and Inclusion, Cheuk constantly organizes workshops and mentored sprints for minority groups. In 2021, Cheuk has become a Python Software Foundation fellow.
Projects
Articles
PyCascade 2023 — PyCascade is not as huge in number as other conferences, but there’s something special about it. Let’s find out! The day I arrived, it is the day before the conference....
DevRelCon Yokohama — My first time speaking at DevRelCon would be in this amazing city! I have always wanted to visit Japan again and this year. DevRelCon in Japan would be in Yokohama....
PyCon Namibia 2023 — I am finally back in this beautiful country and meeting all these awesome people at PyCon Namibia! Day 1 After a long flight that lasts more than 10 hours from...
PyCon France 2023 — It has been 4 years since I gave a keynote at PyCon France, they are welcome to be back with open arms! Day 1 - Sprint I took the first...
State of Open Con 2023 — I was invited to this conference a week ago and I enjoyed it so much! Day 1 To be honest, I was a bit tired just coming back from FOSDEM...
FOSDEM 2023 — After 2 years, FOSDEM is finally back in ULB. So has this biggest Open-Source conference changed? Friday - Fringe events I arrived early on Friday early morning but it seems...
Videos
Untangle Python spaghetti — Untangle Python spaghetti - a dive into environments and dependencies management Once we get started in Python, dependency management becomes a skill that we need to avoid requirement conflicts amongst...
Better Data Governance with Revision Control Workflows — At the beginning of the talk, we will explore the role of revision control in promoting open-source software development. Cheuk will talk about how open-source software contribution is made possible...
Will PyScript replace Django? - What PyScript is and is not — In this talk, through some examples and demos of PyScript, we will see how to use it - just include the CDN URL, understand that it is a frontend-only Python...
PyData Bristol Meetup — Using Numba Effectively Today - Cheuk Ting Ho Have you ever heard of Numba? It is (mainly) a JIT (Just-In-Time) compiler to make your math-heavy Python code run faster under...
PyBerlin 36 - 🍁🍁 Special autumn event. Day 1 🍁🍁 — Using Numba Effectively Today // Cheuk Ting Ho Numba is syntactically easy to use - just add a decorator, but actually very hard to use effectively. The reason being it...
I have to Confess, I still Love Pandas - presented by Cheuk Ting Ho — In this talk, Cheuk will reapproach Pandas as someone who is a fluent user of the library. Cheuk will review why Pandas is useful to work with data and what...
Workshops
This workshop consists of 3 chapters. In each chapter, by walking through hands-on exercises, we can use PyScirpt to create data visualisations and deploy Sci-Kit learn models, which are some of the most common tasks in data sciences.
In this workshop, we gonna go through 3 notebooks (plus an optional NumPy tutorial) to get an idea of the inner working of Numba, try trouble shooting with compilation problems and put them into practice.
Recommendation algorithms are the driving force of many businesses: e-commerce, personalized advertisement, on-demand entertainment. Computer algorithms know what you like and present you with things that are customized for you. Here we will explore how to do that by building a system ourselves.
Storing data in a tabular format is not always ideal. Taking advantage of strong data in knowledge graphs can make handling complex data structure possible and data visualization easier. In this workshop, you will get all the basics to start modelling data in the terms of triples and building schemas of a knowledge graph.
Data scientist love building Shiny apps. It lets you create an interactive dashboard without the complexity of handling javascript or HTML. It also integrates well with other tools for data science as well. If you code in Python and you love Jupyter notebook, I will teach you how to make a “Shiny app” in Jupyter notebook with Python using Bokeh.
In this workshop, we will be using Rasa, an open source machine learning framework, to build a chatbot that will ask for an individual's contact details (compliant to GDPR) and for feedback for an event that they may have attended. Feedback will then be analyse for sentiment and reported in a basic web app.
In this workshop, through exercises, we will learn about (Deep) Reinforcement Learning and how to implement different strategies and train an agent to solve different tasks (or play games) in OpenAI Gym. For the consistency of the environment and make use of a free GPU, we will use Google Colaboratory (Google Account needed)
A step by step guide to making your first pull request (PR) in GitHub. As most open-source projects are hosted on GitHub, it will be the first thing you have to learn if you want to contribute to open-source projects. Also, you will have git setup and learn how to start using git.