Pivot Table Concepts by Derek Mortensen via @TDataScience

Report, Analyze, Tell Stories.

This was really interesting. Pivot tables tell us so many things and can be a great tool and so to be able to do them outside of Excel is great.

WEBINAR: Deploying an Image Classification Model to the OpenMV Camera - 26 July 2022

 

Workshop Series Deploying an Image Classification Model to the OpenMV Camera Register Today Date: Tuesday, July 26, 2022 Time: 9:00 am PDT | 4 pm UTC | 7:00 pm EET Duration: 16 minutes In this IoT Central MicroSession with Edge Impulse, first see how the OpenMV camera is an all-in-one computer vision system that can be programmed with MicroPython. Then learn how to download a trained image classification model from Edge Impulse and deploy it to the OpenMV camera. You will use the OpenMV TensorFlow Lite library to perform inference and use the inference results to perform some action (e.g. write information on the preview screen when a particular object is seen). Instructor: Shawn Hymel, Senior Developer Relations Engineer, Edge Impulse Optional Hardware: OpenMV H7, OpenMV H7 R2, or OpenMV H7 Plus Preparation: Free sign-up at https://studio.edgeimpulse.com/signup Register Today

We take our units of analysis for granted by/via @Randy_Au

In a perfect world, you choose the unit of measurement that is optimal for the question you’re trying to answer in some analysis. But practically, more often than not, this isn’t the case. Take Randy Au’s advice and think twice next time you’re deciding on a unit of measurement.

This is really important. To give a global view of anything inevitably means you will have to do some kind of data conversion between date/times, units of measurements, etc. Let's take a quick example - there are three gallon types - are you talking about imperial gallons, US gallons or even US dry gallons. How do they relate to litres?  Clearly, the chances are that you will need master tables to enable translations between the different values.

Pydantic or dataclasses? Why not both? Convert Between Them by Diego Barba via @TDataScience

Use data classes in your FastAPI projects, and speed up your pydantic model operations.

This was definitely something lacking in my knowledge and I am glad to have that gap now filled. Definitely, something to carefully think about. I'm so glad it gives some examples and sample code.

Statistics and Probability for Data Science by Benjamin Obi Tayo, Ph.D. via @kdnuggets

In this article, he discusses the importance of statistics and probability in data science and machine learning.

This was really clear and easy to understand. It is pitched at a level that should appeal to folks are different levels of understanding.

WEBINAR: Laying the foundation of a Data Lakehouse with AWS Glue, Apache Iceberg and Dremio - 14 July 2022

Laying the foundation of a Data Lakehouse with AWS Glue, Apache Iceberg and Dremio       REGISTER             Thursday, July 14, 2022   9 AM PT / 12 PM ET       Hi there, Moving analytical workloads from the data warehouse to the data lakehouse can save money, make more of your data accessible to your consumers, and provide a better user experience for your data. Three key technologies that enable you to build the foundation of a data lakehouse are AWS Glue, Apache Iceberg, and Dremio. In this webinar, we’ll go through the benefits of a data lakehouse architecture then dive into a live demo where we’ll create Apache Iceberg tables using AWS Glue and then run blazing fast analytics on the table using Dremio.       Speaker         Alex Merced Developer Advocate Dremio

Data Unicorns Are Rare, So Hire These 3 People Instead by Marie Lefevre via @TDataScience

If data engineers are like plumbers, what other skill sets do you need to build your data stack?

This is interesting and might help you to think of things in a slightly different way.