After months of searching, lots of fun (and some less fun) interviews and hours of self-reflection, I am excited to announce I am the new Head of Product at Dropout Labs! 🎉 The interview and decision process was quite iterative and disruptive! I am somewhat to blame for this as I

Hello! We may not know each other, but here you are on my website -- perhaps because you saw a post or someone shared a link. I'm resourceful, determined, intelligent and looking for new challenges. Welcome! Here's more about me, in case it is news to you: [About Me] Co-founder

When I first was introduced to the idea of adversarial learning for security purposes by Clarence Chio's 2016 DEF CON talk and his related open-source library deep-pwning, I immediately started wondering about applications of the field to both make robust and well-tested models, but also as a preventative measure against

I presented a keynote at PyData Warsaw on moving toward interpretable reliable models. The talk was inspired by some of the work I admire in the field as well as a fear that if we do not address interpretable models as a community, we will be factors in our own

Unless you have been avoiding all news, you have likely heard of the coming changes in European privacy regulations which go into effect in May 2018. The changes are covered under the General Data Privacy Regulation Directive, whose final text was made available in May 2016. I presented a talk

I was invited to give a talk at 404 Dublin, a really cool conference joining community groups w/ tech folks and art installations. When thinking of what topics might be of interest to the audience, I selfishly went to one of my (side) passions.. following artists who are doing amazing

Finding ways to determine fake news from real news is a challenge most Natural Language Processing folks I meet and chat with want to solve. There is significant difficulty in doing this properly and without penalizing real news sources. I was discussing this problem with Miguel Martinez-Alvarez on my last

I gave a long and opinionated tutorial at EuroPython 2017 about how we should do unit testing and validation within a data science scope. The GitHub repository for the course (which is part of my O'Reilly Live Online training) is https://github.com/kjam/data-cleaning-101. I will continue editing and

This past Wednesday, I had the pleasure of giving a keynote at EuroPython 2017. I covered a historical view of ethics in computing. The slides are shared here, but it was also recorded so I will post a video when it is available. (Updated: video added!) In addition, a series

Practical Data Cleaning Resources (O'Reilly Live Online Training) This week I will be giving my first O'Reilly Live Online Training via the Safari platform. I'm pretty excited to share some of my favorite data cleaning libraries and tips for validating and testing your data workflows. This post hopes to be

I was kindly asked by the PyData Amsterdam organizers to keynote the conference. As a passionate fan of ethical machine learning and the great research being done by data scientists and academics around the world -- I am very enthused to present the topic to the conference. My slides are

The saddest moment for me at conferences is when I'm in the middle of an interesting conversation with a bright person and I ask her when her talk is and she says, "Who me?" The number of folks I speak with every year at conferences who have amazing

Over the new year holiday time I had a chance to get away from it all, and snuck up to Finland to sit in a lodge on the Gulf of Finland, sip coffee, take saunas and read. I brought along a few books, the only programming one being Brian W.

I'm really excited to announce a new Python video course with O'Reilly on data pipelines. If you are interested in learning some of the popular options available for workflow automation and management in Python, take a look! In the course, I cover: Using Celery for simple automation Setting up Hadoop

PyConCZ 2016 was such a fun conference! First off, it was the first time I got to see Jackie Kazil since we started writing our O'Reilly book Data Wrangling with Python together, HOORAYYYY! OMG PYTHONISTAS! @JackieKazil & I are together for the first time since we started the @OReillyMedia Data

I gave a talk about Directed Acyclic Graphs (DAGs) and Dask at PyConCZ 2016. It was super fun and I had a great time at the conference. If you want to read my slides below, here they are! There will be videos available later, so I'll post the link / video

I participated in a two-day PyDataBerlin Hackathon event in early-October and decided to build a scraper for European Parliament. This was after I found the Europarl parallel corpus a bit underwhelming as it is messy and not tagged for party, speakers or topic (this is understandable, as it is primarily

I dunno about you, but I often find myself bored with NLP (natural language processing) datasets. Too often they are older, based around something that is not particularly interesting to me or something I've analyzed or used before. For me, IRC has often been a source of community, fun, sometimes

I gave a talk at PyCon UK 2016 on automating your data cleanup with Python. I want to again thank the organizers for having me and thank the folks who attended. If you have any questions or are interested in talking about data cleaning problems, feel free to reach out:

You may have read recently about machine learning's bias problem particularly in word embeddings and vectors. It's a massive problem. If you are using word embeddings to generate associative words, phrases or to do comparisons, you should be aware of the biases you are introducing into your work. In preparation

Question: How does it feel to be a woman in tech? Answer: via GIPHY see also: OG PyLadies Interview

I had a great time talking about Sentiment Analysis and Natural Language processing at EuroPython 2016. Here are my slides for your review, feel free to reach out on Twitter or email if you'd like to chat further about NLP, machine learning and sentiment. I look forward to starting more

Like many people, I enjoy travel. With family and friends all across the United States and a home base in Berlin, it’s fairly easy to find a reason to travel -- either globally or within the EU. That said, what I find more difficult is to determine what’s

I'll be in New York on July 13th and 14th, teaching how to "big data" with Python. We'll cover Pandas, Hadoop, PySpark and more on automation, acquisition and managing your data. Early sign ups get a discount so.. sign up below!

Sign up and learn Python with our intensive 2-day courses. Designed to take you from the basics to more advanced data wrangling, we focus on real data problems and examples so you can apply what you learn immediately. Next Course: New York City, July 13-14 Tickets are available on Eventbrite