The JetBrains Blog

The latest updates on all JetBrains products and topics

Cheuk Ting Ho

Cheuk has been a Data Scientist at various companies – a job that demands high numerical and programming skills, especially in Python. Following her passion for the tech community, Cheuk is currently Developer Advocate at JetBrains. She also contributes to multiple open-source libraries like Hypothesis, Pytest, pandas, Polars, PyO3, Jupyter Notebook, and Django.

AI has quickly become one of the most discussed subjects globally – and it now seems to be able to do just about everything for us. Students are asking it to help them with their homework, and lawyers are even using it for case research. AI agents have grown rapidly in popularity due to the widespre…

Faster Python Concurrency in async/await and threading

Want to write faster Python code? Discover the difference between `async/await` and `threading` and how concurrency works in Python with real-world examples.

It often feels like AI is ubiquitous these days. From helping with research to creating a joke, AI seems able to do everything for us. The public response and general opinions about AI are mixed. Some see the negative aspects of AI and frequently wonder, “Will AI take over my job?”, “Could AI steal …

How Do LLMs Benefit Developer Productivity

LLMs are everywhere! I am sure you have heard of large language models (LLMs) and may have seen demonstrations of what they can do. You may have even tried to play with some of the popular ones yourself. No matter your opinion of or experience with LLMs, you cannot deny that they are a popular topic…

Hi everyone, I am Cheuk, your AI Assistant assistant! Jokes aside, I am the new AI Developer Advocate here at JetBrains. My background is in data science and Python, although I have also recently started learning Rust. I am based in London, UK, and I am very excited to join the team.

Learn how to detect anomalies in time series data using different detection models. Explore our step-by-step guide with code examples for various applications.

Anomaly Detection in Machine Learning Using Python

Learn how to detect anomalies in machine learning using Python. Explore key techniques with code examples and visualizations in PyCharm for data science tasks.

Uncover the 6 data science trends shaping 2024 and learn about the most popular machine learning trends and big data tools of the year.

Learn how to use FastAPI for machine learning. Explore the framework's benefits and why it's popular, and understand how to integrate it into your ML workflows.

How to Move From pandas to Polars banners

Considering replacing pandas with Polars? Learn how to make the switch, what to keep in mind, and how PyCharm can help.

The JetBrains Blog

Cheuk Ting Ho

What Is an AI Coding Agent?

Faster Python: Concurrency in async/await and threading

What Can AI Do to Improve Diversity in the Tech Community?

How Do LLMs Benefit Developer Productivity?

Introducing Cheuk Ting Ho – New Developer Advocate

Anomaly Detection in Time Series

Anomaly Detection in Machine Learning Using Python

The State of Data Science 2024: 6 Key Data Science Trends

How to Use FastAPI for Machine Learning

How to Move From pandas to Polars