In this interview I did for the PASS Data Science Virtual Chapter, I talk with Greg Nelson about the five best practice areas of analytics and the importance of design thinking as a tool to help us design and deliver analytic products and services that create value for organizations.
Recently, I delivered a presentation on “Data Science for the Curious” at the WeWork K Street location in Washington, DC.The goal was to help the largely non-technical audience of public policy professionals understand some of the core tenets of data science: its promises and its perils.In light of the recent Facebook revelations, this is more critical now than ever before.
Press the play button below to listen here or visit the show page at DataDriven.tv
Frank and Andy talked about doing a Deep Dive show where they take a deep look into a particular data science technology, term, or methodology. And now, they deliver!
In this very first Deep Dive, Frank and Andy discuss the differences between Data Science and Data Engineering, where they overlap, where they differ, and why so many C-level execs can’t seem to figure out the deltas.
Here’s a great talk on how to use CosmosDB in conjunction with Apache Spark.
This video is an introduction to R programming in which I provide a tutorial on some statistical analysis (specifically using the t-test and linear regression).
It also demonstrates how to use dplyr and ggplot to do data manipulation and data visualization. Its R programming for beginners really and is filled with graphics, quantitative analysis and some explanations as to how statistics work.
If you’re a statistician, into data science or perhaps someone learning bio-stats and thinking about learning to use R for quantitative analysis, then you’ll find this video useful. Importantly, R is free.
With the rapid emergence of digital devices, an unstoppable, invisible force is changing human lives in incredible ways. That force is data. We generated more data in 2017 than in all the previous 5,000 years of human history.
The massive gathering and analyzing of data in real time is allowing us to address some of humanity’s biggest challenges but as Edward Snowden and the release of NSA documents have shown, the accessibility of all this data comes at a steep price.
This documentary captures the promise and peril of this extraordinary knowledge revolution.
If you’re looking for a cloud service to run Jupyter notebooks, then look no further than Azure: notebooks.azure.com
Better yet, it’s free. Yes, free.
Watch this episode of the AI Show to learn more.
Siraj Raval asks Brayden McLean 67 questions about life at Lyft as a Data Scientist.
Ben G Kaiser shares some insight on the differences between data scientists and data analysts.
Missing from his equation: Data Engineers.
If you caught my Data Science for Developers webinar last week, I recorded a quick live stream today about the number one piece of feedback from the audience.
Also, here’s a list of resources I mentioned
- Exploring the Azure Machine Learning Workbench
- Get Smart – Editor’s Note
- Doing Data Science and AI with SQL Server
- Data Science Essentials in Python
- Data Science from Scratch
- Hands on Machine Learning with Sci-kit Learn and TensorFlow
- Advanced Analytics with Spark
Podcasts & YouTube Channels
- Data Driven
- The Data Podcast
- Siraj Raval (great introductory video tutorials and more)
- Data Science for Beginners
- How to become a Data Scientist in 6 months a hacker’s approach to career planning