Home Python PyDev of the Week: Claudia Ng

PyDev of the Week: Claudia Ng

PyDev of the Week: Claudia Ng


This week we welcome Claudia Ng because the PyDev of the Week! Claudia is an creator / contributor at Actual Python! Should you’d wish to see what else Claudia has been as much as, it’s best to try her private web site.

Let’s spend a number of moments attending to know Claudia higher!

Are you able to inform us just a little about your self (hobbies, schooling, and so forth):

I’m an information scientist and I’ve spent the previous 5 years working in fraud and credit score threat within the fintech (monetary expertise) area. I’ve a Masters in Public Coverage from Harvard College and a Bachelor’s in Worldwide Enterprise (Finance) with a minor in Spanish from Northeastern College.

In 2018, I used to be working at a Fintech referred to as Tala, the place I managed the brand new buyer portfolio for his or her Mexico market. It was an unimaginable journey the place we scaled the shopper base by over 500x in solely two years! Via this course of I noticed the ability of automating lending selections enabled by machine studying. I used to be fascinated by how different knowledge could possibly be used to foretell buyer’s compensation behaviors and fraud threat, unlocking the power to lend to people with no or little credit score historical past.

I’m an impact-driven particular person and seeing the ability of utilized ML impressed me to set my thoughts on pivoting into knowledge science by taking up ML-related tasks at work, doing on-line programs and facet tasks, and ultimately transferring onto the information science crew.

I like what I do and out of doors of labor, my hobbies embrace every kind of water sports activities, bouldering and sudoku.

Why did you begin utilizing Python?

I first began utilizing Python in 2019. I used to be initially utilizing R for analyses since I had realized to make use of it in grad college, however the Information Science crew used Python, so I began studying and selecting it up. I discovered it to be extra sturdy and there are various good third-party packages to assist my work. Python is unquestionably my most popular language now!

What different programming languages have you learnt and which is your favourite?

I exploit Python and SQL every day on the job. I’m an enormous language nerd and may communicate 9 human languages if that counts.

What tasks are you engaged on now?

I’m engaged on my second tutorial for Actual Python on kind hints for a number of return varieties in Python. Keep tuned for extra when it comes out!

Which Python libraries are your favourite (core or third celebration)?

I’m a Information Scientist, so I like fairly graphs and visuals. It’s a essential component to with the ability to inform a superb knowledge story and assist with higher decision-making. I’d say that my favourite Python library is plotly. It’s a library for making interactive plots, and I like how versatile it’s.

How did you get began writing articles for Actual Python?

After I pivoted from an analyst position into knowledge science again in 2019, I began writing as a result of I needed to share my learnings and hopefully encourage others with out a STEM diploma to interrupt into knowledge science/ engineering. I used to be writing weblog posts on medium for a number of publications together with In direction of Information Science, In direction of AI and Analytics Vidhya about totally different matters associated to machine studying, characteristic engineering and knowledge visualizations.

In early 2023, I noticed that Actual Python was in search of technical writers and utilized. I used to be a subscriber and realized a lot about programming from Actual Python’s tutorials and programs, it seems like a dream to be writing for this publication!

What excites you most within the knowledge science world proper now?

I’m excited concerning the rise of autoML packages that may automate among the extra tedious components of ML modeling, like knowledge cleansing, mannequin choice and hyperparameter optimization. This might lower down the time spent through the mannequin growth cycle, permitting knowledge scientists to iterate sooner.

Is there the rest you’d wish to say?

If you need to take a look at my work, please go to ds-claudia.com to see previous weblog posts. You too can subscribe totally free to obtain emails once I publish new weblog posts – no spam I promise!

Thanks a lot for doing the interview, Claudia!



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