Run Your Python Code as Fast as C by @mmsbrggr via @TDataScience

How you can supercharge the performance of your python code without changing a thing.

I really loved Marcel's explanation of how PyPy works and the difference in how various pieces of code run. It made it very clear to me.

WEBINAR: How Yum! Brands uses location data from Foursquare to make smarter decisions 06 May 2021

. How Yum! Brands uses location data from Foursquare to make smarter decisions REGISTER NOW . You’re Invited! THURSDAY, MAY 6 11AM PT | 2PM ET 60 MIN SESSION REGISTER NOW Join this webinar to discover how Yum! Brands and other organizations are leveraging location-based data to boost in-app location accuracy, increase in-store foot traffic, and expand ecommerce business. Data and analytics leaders are using third-party data to transform the way they innovate and improve customer experiences. Learn how Yum! Brands is optimizing site selection decisions using Foursquare location data to better understand how local landscapes in foreign market trade areas impact business outcomes. Attendees will learn: How data providers, such as Foursquare, can pinpoint firmographic details such as venue name, address, and category as well as rich content attributes such as photos, reviews, and tips The value received from leveraging ‘visits’ data that provides insight into certain categories, chains, or individual venues How to improve data pipelines for assessing high quality and relevant location-based, third-party data Data analysis strategies as they apply to faster insights and business outcomes Techniques to distill key insights into data visualization tools How and why diverse data can enrich analytics Webinar speakers: Nikhil Jain Senior Director of Decision Sciences, Yum! Brands Nikhil is responsible for all data science and engineering-related initiatives globally, across all the brands. His team focuses on building AI/ML-driven products to solve complex business problems which are used by brands and franchisees globally. Rob Jonas Chief Revenue Officer, Foursquare As Chief Revenue Officer, Rob is responsible for all sales, partnerships, business development, and international markets across Foursquare’s complete product portfolio, driving revenue growth through multi-product customer relationships with leading global brands and enterprises. Noah Schwartz General Manager, Product and Engineering, AWS Data Exchange Noah Schwartz is the GM of Product and Engineering for AWS Data Exchange. He joined AWS in 2017 and has spent most of his career in a role building technology to generate or use data to answer questions across FSI, CPG, and Sports while working at Bloomberg, Dow Jones, and Palantir. Prior to joining AWS, he was the CTO of Bloomberg Sports, Head of R&D at Dow Jones, and Head of Engineering for Risk & Regulatory Data at Bloomberg. Colin Marden Solution Architect, AWS Colin Marden is a Solutions Architect in the Financial Services industry supporting AWS customers in their journey to modernize, transform, and migrate on-premises workloads to the AWS Cloud. Colin is a champion and specialist for Amazon QuickSight and AWS Data Exchange. He regularly works with AWS customers to create data engineering architectures and speaks at AWS and partner events on these subjects of interest. REGISTER NOW © 2021 AWS Marketplace.

Working With Time Series Using SQL by Michael Grogan via @kdnuggets

This article is an overview of using SQL to manipulate time-series data.

This is nice and clear. Times are ok if you have enough of the right data and you really understand what you are doing. Pay particular attention to timezones and daylight saving. Also, consider the physical location of the data and what time that system or server is set up to be. 

Train multiple Time Series Forecasting Models in one line of Python Code by Satyam Kumar via @TDataScience

Develop ARIMA, SARIMAX, FB Prophet, VAR, and ML models using Auto-TS library.

This is really neat - I wish I had known about this library years ago!

6 Python Container Data Types You Should Know by Christopher Tao via @TDataScience

Nailing high-level data structure tools in Python.

This is really useful both for the beginner and the experienced programmer who might appreciate a reminder of these container data types (I certainly did).

Awesome Tricks And Best Practices From Kaggle by Bex T in @kdnuggets

Easily learn what is only learned by hours of search and exploration.

I really think these can be used in "normal" life and that if you don't have access to Kaggle but want to get into Data Science you really need to add it to your places to look for help and advice.

Top 10 Python Libraries Data Scientists should know in 2021 by Terence Shin via @kdnuggets

So many Python libraries exist that offer powerful and efficient foundations for supporting your data science work and machine learning model development. While the list may seem overwhelming, there are certain libraries you should focus your time on, as they are some of the most commonly used today.

I found this useful and it gave me a great reminder of what I can/should use for libraries now.

Pandas Basics Cheat Sheet (2021) by Christopher Zita in @TDataScience

The absolute basics for beginners learning Pandas in 2021.

This is SO useful and a great reminder for you even if you know how to do the basics included in this cheat sheet - definitely one to save and refer back to.

7 Must-Try Data Visualization Libraries in Python by @abhayparashar31 via @BttrProgramming

Tools to help you understand the data well.

I thought this was a really useful post and I learnt a couple more libraries to use next time I need to plot something.

R vs. Python vs. Julia by @daniel_c_moura via @TDataScience

How easy it is to write efficient code?

I found this really insightful and made me think a little more about any code I write.

WEBINAR: AI & Automation for Document Processing in Healthcare - 7 April 2021

 

Sponsored News from Data Science Central

APRIL 7 | 11 AM PT | 2 PM ET Healthcare is a document-intensive industry that generates piles of hard-to-handle unstructured records, making it difficult for organizations to achieve operational excellence and streamline business processes. Join us to strategize on choosing the right document processing solution for your business. Agenda: Healthcare document types and use cases IDP framework: building blocks for document processing solutions The document processing market landscape Methodology for solution evaluation: comparing apples to apples During the webinar, we will offer management and engineering perspectives on document processing with AI, to help you explore available options. Whether you are looking for a ready-made solution or plan to build a custom solution of your own, this webinar will help you find the best fit for your healthcare use cases. RESERVE YOUR SEAT Can’t make it to the webinar? Register anyway to receive the recorded session.

Automate Your Life, Using Web Scraping by Christopher Zita via @Medium

 Christopher shows you 3 unique ways you can save time, using Web Scraping.

This was interesting and a great indicator of what is possible in web scraping to achieve all sorts of things. He includes a link to his course on web scraping on Udemy. I feel some playing with some web scraping to help me to do some rather boring tasks.