PinnedInTDS ArchivebyMinha Hwang·Dec 14, 2022Practical Data Science: Promotion Effectiveness and Promotion Planning—Part 36 Step Process | Step 2 — Prepare Modeling Dataset (1/2)A response icon5A response icon5
PinnedInTDS ArchivebyMinha Hwang·Oct 5, 2022Practical Data Science: Promotion Effectiveness and Promotion Planning — Part 1Business Problem | Key Concepts | Why should we care?
PinnedInTDS ArchivebyMinha Hwang·Dec 11, 2021Cracking Business Case Interviews for Data Scientists — Part 2Issue analysis/work plan, Analyses, Synthesis, and Recommendation
PinnedInTDS ArchivebyMinha Hwang·Sep 6, 2021Cracking Business Case Interviews for Data Scientists — Step 1) Define a ProblemBusiness case study interview questions are often the most difficult part of the interview process, especially for early data scientists…
PinnedInTDS ArchivebyMinha Hwang·Jul 18, 2021Prescriptive Data Science: Beyond Predictive Data Science(1) Descriptive, predictive, and prescriptive data science; (2) Required skillsets and key components in prescriptive data science
InData Science CollectivebyMinha Hwang·Nov 1Improving Enterprise AI and Agent When You Can’t See the DataFour ways to turn eyes-off enterprise data into insights, model updates, evaluations and post-training data, and when each fits chat…
InData Science CollectivebyMinha Hwang·Sep 21Build and Host a Website in 5 Minutes: From Prompt to PublishedA practical guide to creating your first page with AI and putting it online with Netlify or Vercel.
InTDS ArchivebyMinha Hwang·Nov 10, 2022Practical Data Science: Promotion Effectiveness and Promotion Planning — Part 26 Step Process | Step 1 — Build Data FoundationA response icon1A response icon1
InCodeXbyMinha Hwang·Aug 29, 2021Prescriptive Data Science: Single Agent/Static Problem — Joint Price Optimization (1/2)Welcome back. In the previous article, I have described four different types of prescriptive data science problems, which depend on two…A response icon1A response icon1
InTDS ArchivebyMinha Hwang·Aug 6, 2021Prescriptive Data Science 101: Types of ProblemsKey dimensions: single/multiple agents | static/dynamic problems
