Video description
Presented by Caitlin Hudon – Lead Data Scientist at OnlineMedEd
Before AI, before machine learning and pipelines, and before dashboards and BI, an organization starts with a pile of data, some business questions, and a few ideas on how to connect the two — a greenfield, and an entry point for data science.
Answering business questions and turning raw data into insights, models, and products means more than just writing code and doing analysis. A successful data science team needs tools, a communication strategy, thoughtful infrastructure, and a plan to deliver on their goals. This talk will cover how to tackle greenfield data science challenges from the perspective of the first data science hire in an organization, and how to build data science infrastructure from the ground up.
Table of contents
- Building Data Science Infrastructure 00:22:28
Product information
- Title: Building Data Science Infrastructure
- Author(s):
- Release date: March 2020
- Publisher(s): Data Science Salon
- ISBN: 00007ZK3AGMACZS
You might also like
video
Building Effective Data Science Infrastructure in 30 Minutes
Ville Tuulos demonstrates how to develop and deploy a production-grade machine learning application on the fly, …
book
Data Science on AWS
With this practical book, AI and machine learning practitioners will learn how to successfully build and …
book
Building Machine Learning Pipelines
Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t …
video
Mastering Big Data Analytics with PySpark
PySpark helps you perform data analysis at-scale; it enables you to build more scalable analyses and …