Python-bloggers

Pandas vs. dplyr It’s difficult to find the ultimate go-to library for data analysis. Both R and Python provide excellent options, so the question quickly becomes “which data analysis library is the most convenient”. Today’s article aims to answer this question, assuming you’re equally skilled in both ...

Our last post parsed portfolio optimization outputs and examined some of the nuances around the efficient frontier. We noted that when you start building portfolios with a large number of assets, brute force simulation can miss the optimal weighting scheme for a given return or risk profile. While optimization finds ...

In the past, we have provided examples of how to build a Flask Rest API, how to build and deploy ... Read moreHow to Deploy ML Models into AWS with Elastic Beanstalk

Vincent Warmerdam shared this Youtube video which I thoroughly enjoyed watched. It’s about Saul Pwanson, a software engineer whose hobby project got a little out of hand. In 2016, Saul Pwanson designed a plain-text file format for crossword puzzle data, and then spent a couple of months building a micro-data-pipeline, ...

Learn how to explain predictions of convolutional neural networks with PyTorch and SHAP The post PyTorch + SHAP = Explainable Convolutional Neural Networks appeared first on Better Data Science.

Let’s say that we want to create membership cards for our members. In this tutorial, we will show you how ... Read moreAdd Text On An Image using Python

Our last few posts on risk factor models haven’t discussed how we might use such a model in the portfolio optimization process. Indeed, although we’ve touched on mean-variance optimization, efficient frontiers, and maximum Sharpe ratios in this portfolio series, we haven’t discussed portfolio optimization and its outputs ...

In finance, a measure of asset movements against the market is the market beta β. It is a popular measure ... Read moreStocks Market Beta with Rolling Regression