Zâmbetul Soarelui

This is a post in our Your Django Story series where we highlight awesome ladies who work with Django. Read more about it here.

  Katerina Kampardi is a Web Applications Developer from Greece who works as a freelancer. Like many aspiring developers, Katerina is self-taught and got her start with online tutorials. She later attended a Python Specialization. Today, she works on various Django projects as an independent developer. Find her on Github.

How did your story with code start?

It started during my Bachelors Degree in University of Athens when I attempted the Music Technology Specialization. I learned some basic algorithms and how to implement them in C. After that I made the serious decision to change my career plans. I started learning Python over two years ago, primarily from online tutorials.

  What did you do before becoming a programmer?

I was studying/teaching piano and music theory, working mostly with children.

  What do you love the most about coding?

The way that algorithms give all problems a possible solution - however big and complicated the problem seems to be, it can always be divided into smaller pieces to deal with. My favorite thing is to design such solutions with algorithms and then in implement them in whatever programming language. Of course, Python is my favorite one!

  Why Django?

Well, as a freelance web developer, the last four years I have worked with various frameworks and content management systems. I find Django to be the most feature-complete and best-documented framework I’ve worked with. In addition, Django has an exceptional community: everyone is helpful and happy to share what they’ve learned.

  What cool projects are you working on at the moment/planning on working on in the near future?

At the moment I am working with Django Web Framework, in a couple of e-shops and also a custom blog.

I am also planning to start my own web application with Django Rest Framework :)

Alongside this work, I am also trying to help as a contributor to Zulip - a powerful, open source group chat application written in Python. You can view my projects on Github.

  What are you most proud of?

When one of my projects goes on deployment and use, Oh, I feel very proud about it. Also, new coders make me feel proud when I help them - that’s the reason I am planning to organize a Django Girls Event in Greece.

  What do you like doing in your free time? What’s your hobby?

I like play the piano, Latin dancing, and go on bike tours. Since I have a two year old son, I try to spend as much quality time as I can with him. :)

  Do you have any advice/tips for programming beginners?

At present, I don’t consider myself enough of a senior coder to give others advice. But if you must know, I would say: “Code, Code, Code!” …Oh, and Code some more. But, importantly: don’t go it alone. Get started with tutorials, find a mentor, start a bootcamp or online class, and read books. That is exactly what I am doing. And please remember: it is never too late!!!

How did attending a Django Girls workshop influence your life/career?

I haven’t attended or organized a Django Girls workshop experience yet, but I am planning to do so this autumn in Greece. More details to come!

  Thank you so much, Katerina!

  If you would like to suggest someone to be featured in the Your Django Story series (or would like to nominate yourself!), please email us at [email protected]!

Adrienne Lowe

This is a post in our Your Django Story series where we highlight awesome ladies who work with Django. Read more about it here.

Jessica is a startup founder, software engineer, and open source developer living in San Francisco, California. She enjoys the Internet, networking, low-level systems engineering, relational databases, tinkering on electronics projects, and contributing to and helping other people contribute to open source software. Jessica spends a lot of time volunteering, engaging technologists about education, and empowering effective people and initiatives in her capacity as a Director for the Python Software Foundation.

How did your story with code start? What did you do before becoming a programmer?

I always liked computers (there’s a famous family photo of me at age 2, holding a bottle in 1 hand and playing on an Apple IIci with the other). I took an introductory programming class in high school, but I have to admit that it didn’t really click with me – I didn’t have any friends who were into programming, and I was much more into the sciences; I was a Science Olympiad nerd, and I declared Chemistry as my first major in university.

While pursuing a Chemistry degree at MIT, many of my friends were pursuing Computer Science degrees. I liked Chemistry, but I was intrigued by the observation that my CS friends seemed to be learning a toolkit of tools for solving countless interdisciplinary problems in the world. That was powerful, and I wanted to see if I could do it too. I signed up for a few CS classes, loved them, and ended up getting bachelors and masters degrees in Computer Science.

  What do you love the most about coding?

I love the ability it gives me to effect changes I want to see in the world. We can write software that makes people’s lives better, that connects people, that empowers people with data.

  Why Django?

95% of the time, what I need is a database-backed website with administrator support, and Django lets me get up and running in just a few hours. It is batteries-included in the ways I most need it to be, just like Python.

  What cool projects are you working on at the moment/planning on working on in the near future?

Recently, I’ve been prepping for a couple of PyCon talks and going through Capture the Flag challenges.

I’m grateful that I’ve been able to speak at PyCons around the world, which is a chance to meet and learn from the local Python and open source communities.

  What do you like doing in your free time? What’s your hobby?

I spend a lot of my free time reading and writing. I’m also a Director for the Python Software Foundation (PSF) and co-chair of the PSF’s Outreach and Education Committee.

  Do you have any advice/tips for programming beginners?

Everyone can become a good programmer. It takes time and practice to become fluent, just like with a foreign language, but you’ll get there!

Once you know the language basics, most people find that the best way to get better quickly is to practice through projects that they actually care about. Pick a project, and see what completing that project forces you to learn.

Thanks Jessica! :)

Annabell Ossowski

“Their first code review”.

William Frederick Yeames, oil on canvas, 1878.

moodboard: hermione granger

“I made wine from the lilac tree, put my heart in its recipe, it makes me see what I want to see, and be what I want to be.”

By Suju Rajan

Data is the lifeblood of research in machine learning. However, access to truly large-scale datasets is a privilege that has been traditionally reserved for machine learning researchers and data scientists working at large companies – and out of reach for most academic researchers.

Research scientists at Yahoo Labs have long enjoyed working on large-scale machine learning problems inspired by consumer-facing products. This has enabled us to advance the thinking in areas such as search ranking, computational advertising, information retrieval, and core machine learning. A key aspect of interest to the external research community has been the application of new algorithms and methodologies to production traffic and to large-scale datasets gathered from real products.

Today, we are proud to announce the public release of the largest-ever machine learning dataset to the research community. The dataset stands at a massive ~110B events (13.5TB uncompressed) of anonymized user-news item interaction data, collected by recording the user-news item interactions of about 20M users from February 2015 to May 2015.

The Yahoo News Feed dataset is a collection based on a sample of anonymized user interactions on the news feeds of several Yahoo properties, including the Yahoo homepage, Yahoo News, Yahoo Sports, Yahoo Finance, Yahoo Movies, and Yahoo Real Estate.

The news feed on Yahoo’s homepage

Our goals are to promote independent research in the fields of large-scale machine learning and recommender systems, and to help level the playing field between industrial and academic research. The dataset is available as part of the Yahoo Labs Webscope data-sharing program, which is a reference library of scientifically-useful datasets comprising anonymized user data for non-commercial use.

In addition to the interaction data, we are providing categorized demographic information (age range, gender, and generalized geographic data) for a subset of the anonymized users. On the item side, we are releasing the title, summary, and key-phrases of the pertinent news article. The interaction data is timestamped with the relevant local time and also contains partial information about the device on which the user accessed the news feeds, which allows for interesting work in contextual recommendation and temporal data mining.

The Personalization Science team at Yahoo Labs has had a ton of fun working on a full-scale version of the Yahoo News Feed dataset, which has sparked some compelling ideas (e.g. Birds, Apps, and Users: Scalable Factorization Machines and Science Powering Product and Personalization: Going Beyond Clicks) in the areas of behavior modeling, recommender systems, large-scale and distributed machine learning, ranking, online algorithms, content modeling, and time-series mining.

We hope that this data release will similarly inspire our fellow researchers, data scientists, and machine learning enthusiasts in academia, and help validate their models on an extensive, “real-world” dataset. We strongly believe that this dataset can become the benchmark for large-scale machine learning and recommender systems, and we look forward to hearing from the community about their applications of our data.

Happy (large-scale) machine learning in 2016!