PinnedJose ParreñoLearning to rank: my written and favourite articlesLTR is a specialised domain in ML. Here, I capture a list of my favourite resources to help in your ranking journey.Jul 29Jul 29
PinnedJose ParreñoMarketing and bidding science: my written and favourite articlesThere is not much content out there about paid marketing and bidding from a DS & ML perspective. I hope I can help with my articles.Jul 29Jul 29
PinnedJose ParreñoData visualisation: my written and favourite articlesAll my written articles about data visualisation best practices, Streamlit and Plotly. It’s a live document, stay tuned for more additions!Jul 29Jul 29
PinnedJose ParreñoData Science team management: my written and favourite articlesThis blog captures all my written articles about leading DS and ML teams. It’s a live document, so stay tuned for more additions!Jul 29Jul 29
Jose ParreñoinTowards Data ScienceHow to Create Well-Styled Streamlit Dataframes, Part 1: Using the Pandas StylerStreamlit and the pandas Styler object are not friends. But, we will change that!15h ago15h ago
Jose ParreñoBook summary: Storytelling with data by Cole NussbaumerExtracting the main learning points and examples from my go-to data visualisation book.Aug 7Aug 7
Jose ParreñoAdjusting CPCs based on binary multipliersOptimize algorithmic bidding with binary multipliers, even if they are constrained with minimum floors.Jul 27Jul 27
Jose ParreñoBidding 101 formulas you should knowUnlock bidding success in paid marketing! Discover CPC, CPA, and ROAS formulas with our easy-to-use calculator. Get the basics right!Jul 19Jul 19
Jose ParreñoHow to calculate elasticity of bids in PPC marketingMaster PPC bid elasticity! Discover techniques to normalize metrics, handle non-linear trends, and ensure smooth, positive elasticity.Jul 17Jul 17
Jose ParreñoTips for Streamlit learnt the hard wayTransform your Streamlit experience with these top tips: from multipage simplicity to efficient caching and sleek layouts. Let’s dive in!Jul 10Jul 10