Data Elixir - Data Elixir - Issue 427
ISSUE 427 · March 7, 2023ProjectsSuspicion Machines MethodologyWired Magazine recently released a four-part series about the inner workings of a welfare fraud detection system. They got access to not just the algorithms but also the data that powered the system and the handbook that was used by the data scientists who ran it. This post is a detailed explainer on what the researchers did and how they did it. Using ML to Aid Survivors and Race through TimeA few hours after the recent earthquakes in Turkey, a group of data scientists and engineers built a machine learning application to help search and rescue teams find survivors. This a great post that details the problems they helped solve, the issues they encountered along the way, and how they ultimately succeeded. Sponsored LinkGain productivity, accelerate innovation, and improve customer experiences.You're invited! Experts in financial data showcase how to utilize rich third-party data in our upcoming events. Discover why wealth advisory firms, banks, and business lenders leverage cloud-based technology and data-driven insights to make important business decisions. Webinar: How to harness financial data to help drive improved analytics and insights with Envestnet & AWS Date: March 22nd Time: 10:00 AM (PST), 10:00 AM (BST), AND 10:00 AM (SGT) Have a product, service, job, or event you'd like to share with Data Elixir readers?Sponsor an Issue | Talent CollectiveTutorials & OpinionsPredicting wine quality using chemical propertiesNice step-by-step tutorial for building a model to predict wine quality in Python. Covers data normalization, Pytorch basics, training, visualization, model evaluation, and how to use the model to make predictions. There's a link at the bottom of the post to a notebook. Onboarding is an art, not a scienceEffectively onboarding new members onto a data team can go a long way to set them up for success. This post breaks down what new team members need to know and a timeline for coming up to speed. The considerations here apply to both sides of the table so if you're the one joining a new team, this is a good framework for learning your new job. Julia and Python better togetherHere's how to use Julia and keep using the Python packages you like as a part of your Julia workflow. Sharpen your math, CS and data skills in 15 minutes a dayFor professionals and lifelong learners alike, Brilliant is one of the best ways to learn. The deets: Bite-sized interactive lessons make it easy to level up in everything from math and data science to AI and beyond. Join 10+ million people building skills every day. Start your 30-day free trial today! Tools & CodeMathesarMathesar is a new open source tool that provides a spreadsheet-like interface to a PostgreSQL database. It's a self-hosted web application, which gives you privacy and control of your data. Check out the live demo. This is nice! sqlean - All the Missing SQLite FunctionsThere are a lot of SQLite extensions out there, but they are incomplete, inconsistent and scattered across the internet. sqlean brings them together, neatly packaged into domain modules, documented, tested, and built for Linux, Windows and macOS. MeerkatMeerkat is an open-source Python library that helps to interactively wrangle images, videos, text documents and more with foundation models. With Meerkat, you can pull in unstructured data, wrangle it with foundation models, and build custom, interactive workflows, all from Python. If you have 3+ years of data science experience, join the Data Elixir Talent Collective where top companies apply to you. For details, check out the Collective 👉ResourcesDatasets at your fingertips in Google SearchDataset Search is a search engine for datasets. Using just keywords, users can search from a variety of sources, including scientific government, and commercial datasets. There are more than 45 million datasets here and everything is well documented and easy to find. Was this email forwarded to you? Sign up here >> |
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Data Elixir - Issue 426
Tuesday, February 28, 2023
Awesome Polars. Patterns for content moderation. Fundamentals of data viz. New machine setup for DS. Data-Centric AI.
Data Elixir - Issue 425
Tuesday, February 21, 2023
New MAD landscape. EDA for Jupyter. Data salary benchmark for Europe. Get old code running again. ggplot2 tricks. Creating a data cleaning workflow.
Data Elixir - Issue 424
Tuesday, February 14, 2023
Big Data is dead. GPT from scratch. How to be incognito in 2023. Sports analytics. Intro to geospatial data.
Data Elixir - Issue 423
Tuesday, February 7, 2023
Faster A/B decisions. Soccer Analytics Handbook. Getting started with LLMs. Floating point problems. Critiquing data viz.
Data Elixir - Issue 422
Tuesday, January 31, 2023
Illustrated pandas. Simpson's paradox. How to approach resumes. The GPT analyst. Accelerating A/B tests.
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