{inner, outer, left, right}Photo by Sid Balachandran on UnsplashIn 2008, Wes Mckinney was at the Hedge Fund AQR and developed a small piece of software which became the pre-cursor to Pandas, developing and finalising it later on. Since then, Pandas has become one of the most important Python libraries that most Data Scientists (if not all) use... Continue Reading →
The Intersection of Statistical Physics and Machine Learning
Living in Higher DimensionsPhoto by Greg Rakozy on UnsplashSir Professor David Mackay revolutionised Machine Learning. There’s no question about it. His abundance of knowledge was clear from his research, his selflessness, and his groundbreaking work on Information Theory. Both the fields of Gaussian Processes and Neural Networks owe him a lot.During my studies I came across... Continue Reading →
Sorry, the TensorFlow Developer Certificate is Pointless
Plenty of Better Alternatives Exist to Prove your SkillsetPhoto by Daniel Mingook Kim on UnsplashGoogle’s overall openness and investment in the space of AI has been phenomenal. I really think that unequivocally, the whole world has a lot to thank them for. Academic breakthroughs are published and code is often made free on GitHub. What more could... Continue Reading →
Ternary Conditional Operators in Python
Mastering Efficient List and Dictionary ComprehensionPhoto by Belinda Fewings on UnsplashPython is versatile to use and its goal is to make development easier for the user. Compared to C# or Java which are notoriously cumbersome to master, Python is relatively easy to get good at. Moreover, it’s relatively easy to get pretty damn good at.List and... Continue Reading →
What does “__name__” mean in Python?
How and why we use __name__=='__main__'Photo by Nick Fewings on UnsplashPython is such a popular language because it’s easy to use and it’s comprehensive. Previously, I covered what the keyword yield was useful for and with some great feedback, I have decided to tackle another key feature: __name__ .Let’s get straight to it.Now quite often you’ll see a... Continue Reading →
What does the keyword “yield” do in Python?
Handling Python Memory Issues when faced with Big DataSmileys [Pixabay]As the programming language Python develops over time, added functionality improves both its usability and performance. Python has become (if not) the foremost language in the Data Science and its handling of big data sets is amongst one of the reasons why.It’s no wonder that the language... Continue Reading →