3 Common Technical Debts in Machine Learning and How to Avoid Them
Technical debt is the ongoing cost of expedient decisions made when implementing code. It is all the shortcuts or workarounds in technical decisions that give short-term benefit in earlier software
The 1 Cycle Policy
The 1cycle policy gives very fast results when training complex models. It follows the Cyclical Learning Rate (CLR) to obtain faster training time with regularization effect but with a slight modification.
An implementation guide to Word2Vec using NumPy and Google Sheets
Word2Vec is touted as one of the biggest, most recent breakthrough in the field of Natural Language Processing (NLP). The concept is simple, elegant and (relatively) easy to grasp. A