In many practical applications, assuming a linear relationship between variables can simplify problem solving significantly. During a recent project I learned things can go wrong when this assumption is made silently while the real world out there turns out to behave non-linear.
It has been a month since I bought a new laptop, a Lenovo Thinkpad T470. Time has come for a small hands-on review.
Earlier this year we worked with a couple of data scientists on the prediction of financial markets. Our project, nicknamed Back2Future, aimed at getting a better understanding of the price movements at foreign exchange markets (Forex).
An ensemble model can significantly improve the reliability of your decisions. No wonder this powerful concept drives common machine learning models like random forest and gradient boost. But how can you explain your grandma why ensemble models are so useful?
At the time of writing, the Python Package Index hosts more than 120,000 packages. A stunning number that raises the following question: which Python packages should I use to get the job done?