Right now, Python is the prevalent language of AI: a de facto standard for any one who wants to work in data science. From data analysis and visualization to complex deep neural networks, you can do anything with this easy-to-learn, free, open source, understandable, versatile, and library-rich scripting language. The language is not limited to
Opportunities in AI, like so many other fields, are not equally distributed. Only 12% of AI professionals all over the globe are female. Knowing these surprisingly bad stats, We decided to introduce some of the most powerful women leading the field of AI in our blog and started with four brilliant scientists and entrepreneurs in
There are too few women in STEM fields. Many of us have heard this. However, the extent of this inequality in the AI field may still surprise us. In fact, just about 12 percent of AI researchers all over the world are female. Several plans have been shaped in either developed or developing countries to
So you’ve started learning data science, and maybe have watched a few video’s of an online course, read a few chapters, or even taken some university courses. The most important step now is to take what you’ve learned to action ASAP. Do, you must now. Here we have gathered a few datasets for beginner projects
We all make mistakes and we all know that mistakes are meant to be learned from. It’s Okay to make them, and you will do so many times. Thus we decided to tell you about a few common, well-known mistakes so that you can make your own, different mistakes and actually learn new things:) 1
For hundreds of years, archeologists have found and curated historical artifacts for museums. grouping and sorting hundreds of pieces of broken, hardly recognizable ancient artifacts has always been a part of an archeologist's job. It takes a lot of knowledge in the field of archeological typology, and hundreds of hours of tedious manual work to
As everybody says, data science is a fast-evolving and rapidly expanding field. This makes being in sync with the current technical and theoretical progress a priority for every one of us. And while the books are almost always a year or two behind, reading the newest papers is the best way to update your knowledge.
When we started to write a series of blog posts for new data scientists in our blog, we didn’t think it would get more than three or four weekly posts. However, the material was useful to so many of our friends, and ourselves too. In the last weeks, we introduced some of the best places
AI and the faults on earth: Scientists using machine learning to understand the structure and behavior of earthquakes
Earthquakes are a source of danger for billions of people on our planet. While a myriad of them happen every day without any effect on our lives or even without being sensed, a few ones make the skin of the earth shiver and crack deeply… and a few of those come out into our cities.
Our short list of recommended newsletters for the data scientists who want to be in pace with the edge of science
We are all looking for exciting and informative articles to read in our free time. On the other hand, we are also tired of deleting emails that suggest articles we never read. In this article, we help find newsletters that bring the articles you are looking for into your inbox, and we are sure you