Project completed in week 4 (19.10.-23.10.20) of the Data Science Bootcamp at Spiced Academy in Berlin.
I was super excited about this week, because it was about language models and first steps into NLP, my favorite ML topic! The challenge was to create a Python program that scrapes lyrics from a website, preprocesses them, and predicts the artist from the text.
Project completed in week 3 (12.10.-16.10.20) of the Data Science Bootcamp at Spiced Academy in Berlin.
I really enjoyed this week's project for two main reasons: it involved time series analysis and it solved a real-world practical business problem.
Project completed in week 2 (05.10.-09.10.20) of the Data Science Bootcamp at Spiced Academy in Berlin.
On the second week of the bootcamp, we started with Machine Learning (ML). If you think about it, ML surrounds us in everyday life: Netflix recommending you movies you might like, your smartphone camera detecting faces, self-driving cars recognizing passengers on the street, bank detecting credit card fraud -- these are all applications of ML. They can be split into three main ML categories:
This week we focused only on classification and applied logistic regression, decision tree, and random forest models on the Titanic dataset to predict passenger survival.
Project completed in week 1 (28.09.-02.10.20) of the Data Science Bootcamp at Spiced Academy in Berlin.
Our first bootcamp project was creating an animated scatterplot, using the libraries matplotlib or seaborn and imageio. The scatterplot illustrates the relationship between life expectancy and fertility rate of world's countries from 1960 to 2015, based on the Gapminder data set.
Artificial Intelligence is undoubtedly an exciting field. We are making machines think like humans, mimic our actions, and solve problems more efficiently than us, at this at an unprecedented level and speed. But beyond the hype, I can’t help but wonder: does more efficiently mean better? Are some of our actions worthy of being mimicked? And should some of our ways of thinking about the world even be reinforced?
Women in Data is an international non-profit organization dedicated to increasing diversity in data-related careers by organizing conferences, networking events, and mentorship programs around the world. The Berlin Chapter of WiD was just founded in May this year and I was very excited to join as a Marketing Coordinator.
It is a truth universally acknowledged that a data scientist in possession of a good portfolio must be in want of a job. A curated selection of your projects is the best way to showcase your work, interests, and thinking to potential employers. But what makes a "good portfolio"?
From my experience and discussions with colleagues, I summed up four tips that you should apply to make your data science portfolio stand out from the crowd.
We Are Developers is the world’s largest conference for software development. It’s a great opportunity for software engineers to connect with tech companies and learn about interesting advances in technology. This year, WAD was supposed to take place in Berlin, but due to COVID-19, the event was moved online for a Live Week (25-29 May) of exciting talks on different tech topics.
On the second day, I tuned in to watch Adrian Spataru‘s and Bohdan Andrusyak‘s talk The pitfalls of Deep Learning – when Neural Networks are not the solution.
We Are Developers is the world's largest conference for software development. It's a great opportunity for software engineers to connect with tech companies and learn about interesting advances in technology. This year, it was supposed to take place in Berlin, but due to COVID-19, it was moved online for a Live Week (25-29 May) of exciting talks on different tech topics.
On the first day, I tuned in to watch Christoph Pirringer's talk on Diversity in Development: Which hurdles can we overcome right now to open up development?
If you're reading this post around its publishing date in April 2020, chances are you're at home, responsibly isolating yourself amid COVID-19 curfews around the world. What a better time than now to read actual books on data-related topics, that you've been postponing for too long in favor of short articles...
To give you some food for thought for these days, I curated a top 10 list of books straight from my bookshelves.