5 Difficult Skills That Pay Off Exponentially in Programming by Pen Magnet via @Medium

 Go slow, but never stop.

I found this interesting and I think if you can get your head around these five skills it will definitely help your coding moving forward.

Everything About Python Set Data Structure: Beginner’s Guide — PyShark by Misha Sv via TDataScience

In this article we will focus on a complete walkthrough of a Python set data structure.

This is useful for beginners as well as anyone who feels that they need some kind of reminder on how it works.

Mito: One of the Coolest Python Libraries You Have Ever Seen by Ismael Araujo via @TDataScience

Here is Ismael Araujo's take on this cool Python library and why you should give it a try.

It does look interesting, saves so much time and I certainly want to play more with it as I already can see how useful it is but I'm sure I could achieve much more if I understood it better.

10 Regression Metrics Data Scientist Must Know (Python-Sklearn Code Included) by T Z J Y via @Medium

A great article that definitely needs to be added to your notes and kept for reference. I've printed it and put it in a folder and also added it to my Evernote so I can refer back to it when needed.

Storm in the stratosphere: how the cloud will be reshuffled by/via @bernhardsson

Do you think cloud stack consolidation is inevitable? Here's a reasonable take on how the next few years could play out.

I think these are reasonable ideas as I'm sure if it doesn't go exactly this way a fair proportion of it is right.

Calendar Heatmaps : A perfect way to display your time-series quantitative data by Harshita Garg via @Medium

A quick and simple guide to create calendar heatmaps using Python libraries and add interactivity using widgets.

I think these are a powerful way for displaying data and a good way of visualising any anaysis.

20 Amazing GitHub Repositories Every Developer Should Follow by @KamaruzzMd via @Medium

A collection of GitHub repositories to improve your development skill and boost your career.

An absolute wealth of information sources and help for everyone here - even if you are not a full-time developer. Go take a look and I'm certain you will find at least one that is right for you.

WEBINAR: Data Privacy using AI-Driven Data Catalogs - 14 December 2021

 

Sponsored News from Data Science Central

Data Privacy using AI-Driven Data Catalogs What: A free online webinar exclusively for IT Pros When: Tuesday, December 14th, 8:30 AM PST / 11:30 AM EST Where: From the convenience of your personal computer  Register Now Do you have your Enterprise’s data privacy under control? Do you know what datasets are sensitive and who has access? Many companies are behind on privacy and regulatory compliance (GDPR, CCPA, etc.). Legacy tools and manual processes are inaccurate and error prone and can force you to choose between delaying data access by months, or increased compliance risk. Join us for this latest Data Science Central webinar to learn how an AI-driven data catalog can automate sensitive data discovery and apply business rules to help get data privacy and compliance under control. Speakers: Nerea Palacio, Data Protection Officer & Senior Regional Counsel, Hitachi Vantara Glen Martin, Lumada SaaS Master Product Management, Hitachi Vantara

if __name__ == “__main__” in Python Explained Simply by Zlliu via @Medium

If you just started learning Python, you’ve probably come across something like this command already.

I found this useful and it helped to clarify a few things for me in understanding what can happen inside an IF statement.

5 Must-Know Terms in Time Series Analysis by @snr14 via @TDataScience

A fundamental part of data science.

This would a useful reminder/quick tutor in time series analysis. Make sure you also think hard about the method you want to use to plot this analysis as sometimes the graph or notation you use can help of hinder your understanding.

5 Jupyter Extensions to Improve your Productivity by @CornelliusYW by @TDataScience

These packages would extend the Jupyter Notebook Functionality.

These are definitely worth a test and assessment as I think they will make your life much easier in Jupyter.

Why You Should Use Context Managers in Python by Artemis Nika via @TDataScience

Implementing and using context managers in Python.

A good reminder of what one is, their advantage and why you should use one.

WEBINAR: Future-Proofing Your Analytics Investment through AI and Cloud - 1 December 2021

 

Sponsored News from Data Science Central Future-Proofing Your Analytics Investment through AI and Cloud What: A free online webinar exclusively for IT Pros When: Thursday, December 1st, 9 AM PST / 12 PM EST Where: From the convenience of your personal computer  Register Now In this latest Data Science Central webinar, taking advantage of the newest innovations across the business intelligence and analytics landscape is critical to stay ahead of the competition and drive real value from your data. AI, machine learning, and cloud are all raising the bar, and you can position yourself to take advantage of these new capabilities now and in the future. Join Wayne Eckerson from the Eckerson Group along with Chris Mabardy and Denise LaForgia from Qlik as they explore how the BI market is evolving, and the key technologies that will unlock the value of your data for everyone. Topics discussed will include: - The importance of augmented analytics that leverage AI and natural language processing - How automated machine learning can bring the power of data science to analytics teams - Why the rise of cloud analytics is critical to harnessing BI innovation Register today to get our insights on the evolving BI market and future proofing your BI investment.  Speakers: Wayne Eckerson, President, Eckerson Group Chris Mabardy, Senior Director Product Marketing, Qlik Denise LaForgia, Director of Product Marketing, Qlik

Five Advanced Plots in Python — Matplotlib by @rashida048 via @TDataScience

Interactive 3d Plots with Examples.

Very useful and I especially love that there are examples that always help me to apply them to my own work.

20 Python Libraries Every Data Scientist Use by Sara A. Metwalli via @Medium

Whether you're new to data science or not, you must be using some of these libraries.

I looked at this list and realised that there were some I had missed and that I could do some things in an easier/better way using a different library.

All Machine Learning Algorithms You Should Know in 2022 by Terence Shin via @TDataScience

Intuitive explanations of the most popular machine learning models.

This is really useful and definitely worth a read in case there is something new you haven't seen or come across yet. I particularly like that they are grouped into the type of algorithm.

A Guide to 14 Different Data Science Jobs by Nate Rosidi via @kdnuggets

The field of data science is growing into one that features a variety of job titles This guide reviews different positions available for you to consider if you have a data science background.

Definitely worth a read as there are some great jobs out there that are NOT a data scientist but probably suit you and your skillset much better. I think I am closer to a data engineer a lot of the time, but not exclusively.

WEBINAR: Factory 5.0: ML-Powered Manufacturing Workshop - 18 November 2021

 

Workshop Series Click Here to Register Title: Factory 5.0: ML-Powered Manufacturing Workshop  Date: Thursday, November 18, 2021 Time: 8:00 am PST/ 4:00 pm UTC Duration: 120 minutes   SUMMARY This live two-hour workshop is hosted by Arduino PRO’s enterprise-class hardware and Edge Impulse, the world’s leading embedded ML platform for the enterprise. This workshop caters to professionals who are seeking to learn how to build AI-powered solutions for manufacturing processes. Paying participants will receive an official Edge Impulse certificate signed by the CEO, which will be mailed to every registrant who attends and completes the workshop.  Overview: Smart Industry is here and it's helping almost every industry do a lot more with a lot less. From logistics, manufacturing, automotive, retail, oil & gas, pharma, to medicine, companies can start the process of digitization step by step just using the visual data they have accumulated via cameras, advanced MCUs, and machine learning. Such AI-powered systems can provide more than just accurate results but can help humans get more done, eliminating mundane and repetitive tasks.  Sample use cases that can be applied to most other industries: Learn how to apply computer vision to determine counterfeit  Scan for defective goods during the packaging processes Use machine vision to find objects or humans in restricted areas Use computer vision for quality control of pests in agriculture Apply computer vision for maintaining security perimeters Deploy AI to control the goods on the shelves of the supermarket Hardware: Core Board: Arduino Portenta H7 Lite Vision Shield: Arduino Portenta Vision Shield - Ethernet Instructor: Louis Moreau, User Success Engineer, Edge Impulse Guest: Andrea Richetta, Head of Arduino PRO Customer Success   Click Here to Register

Visualizing NYS COVID-19 Data by Meagvo via @TDataScience

With Python Matplotlib and Plotly.

Yes, this focuses on the covid data but it could just as easily be applied to any other data. Use this as a guide on how to do data validation for any other data.

WEBINAR: Hidden Context, Adding Information Without Cluttering Your Dashboard - 18 November 2021

 

Sponsored News from Data Science Central

Hidden Context, Adding Information Without Cluttering Your Dashboard What: A free online webinar exclusively for IT Pros When: Thursday, November 18th, 8 AM PST / 11 AM EST Where: From the convenience of your personal computer  Register Now Sometimes, your dashboard needs a little more explanation for your user. But it doesn’t need to appear on the dashboard all at once. In this latest Data Science Central Webinar, we will uncover a few techniques you can use to add information and update visuals behind the scenes, leaving you with a clean dashboard every time! Join Sedale McCall, Director of Digital Insights at Tableau, as they explain how to effectively add information without cluttering your dashboard.

Bamboolib: One of the Most Useful Python Libraries You Have Ever Seen Here is my take on this cool Python by Ismael Araujo via @TDataScience

Here is his take on this cool Python library and why you should give it a try.

I thought this was a really useful library and definitely worth a try to see if it can help you. I definitely thought it was worth using as it made life a little easier.

WEBINAR: Fast and Fearless - The Future of IoT Software Development Part 4 of 4: IoT Security Solidified and Simplified 16 November 2021

 

Webinar Series Click Here to Register Title: Fast and Fearless - The Future of IoT Software Development Part 4 of 4: IoT Security Solidified and Simplified Date: Tuesday, November 16, 2021 Time: 8:00 am PDT/ 3:00 pm UTC Duration: 60 minutes   SUMMARY The IoT is transforming the software landscape. What was a relatively straightforward embedded software stack, has been revolutionized due to the IoT where developers juggle specialized workloads, security, machine learning, real-time connectivity, managing devices in the field - the list goes on. How can our industry help developers prototype ‘fearlessly’ because the tools and platforms allow them to navigate varying IoT components? How can developers move to production quickly, capitalizing on innovation opportunities in emerging IoT markets? This webinar series will take you through the fundamental steps, tools and opportunities for simplifying IoT development. Each webinar will be a panel discussion with industry experts who will share their experience and development tips on a specific topic. This session will cover how to simplify IoT security.   Click Here to Register

How Netflix uses A/B tests to inform decisions and continuously innovate by/via @NetflixEng

Here are the first four parts in the multi-part series from the Netflix blog on how they use A/B tests to innovate their products.

#1 Decision Making at Netflix

#2 What is an A/B Test?

#3 Interpreting A/B test results: false positives and statistical significance

#4 Interpreting A/B test results: false negatives and power

I strongly recommend that you follow the Netflix blog as you will find a lot of really great educational information that are not just dry lessons but are based on real-life knowledge and experience.

The Match-Case In Python 3.10 Is Not That Simple by Christopher Tao via @TDataScience

7 examples to show the “MATCH case” is not “SWITCH case”

This is really useful and cleverly shows the differences between the two commands.

WEBINAR: Gain Insights from SAP Data with Qlik and Microsoft - 8 November 2021

 

Sponsored News from Data Science Central   Webinar: Gain Insights from SAP Data with Qlik and Microsoft Enterprises are inundated with massive amounts of SAP data and challenged to create more consumable insights without increasing headcount or system resources. It is a daunting task to deal with slow systems and manual coding to gain any value from historical data spanning thousands of products, customers, sales history, and the list goes on. In this webinar, you’ll hear how global manufacturer Greene Tweed developed an efficient, cost-effective, and logical strategy to connect Qlik Data integration and Microsoft Azure Synapse to build an intelligent supply chain for better business insight. Learn how Greene Tweed addressed their challenges and how they use data liberated from SAP for strategic analytics initiatives. In addition, you will discover: How to create a plan of attack to extract insights from massive amounts of SAP data How important change data capture is to building low latency extracts for massive data volumes Why automation with Qlik Data Integration is crucial to expedite data availability How SAP data drives insights to optimize Manufacturing & Supply Chain The gains Greene Tweed realized by moving SAP data to Azure Synapse Register Today Speakers: Matt Hayes, VP of SAP Business, Qlik David Hufnagle, Manager, Enterprise Data and Analytics, Greene Tweed Greg Vigil, Industry Solution Director – Manufacturing, Microsoft Hope to see you there, Sean Welch Data Science Central

Write Better And Faster Python Using Einstein Notation by Bilal Himite via @TDataScience

Make your code more readable, concise, and efficient using “einsum”

I had never heard of this and was fascinated to find out more. I also found this additional article useful:

Understanding einsum for Deep learning: implement a transformer with multi-head self-attention from scratch

Stop Using CSVs for Storage — This File Format Is 150 Times Faster by Dario Radečić via @TDataScience

CSV’s are costing you time, disk space, and money. It’s time to end it.

Definitely, CSVs are great if you want to edit the file but it's not that fast - even a text file is faster.

WEBINAR: Maximizing Data Labeling Operations in High-Stakes Industries: Tips for Tools and Teams - 2 November 2021

 

Are you interested in learning about overcoming data annotation challenges like scaling teams, labeling complex data, and handling edge cases?

There's an art and science to choosing the processes and teams used to extract and structure the data found in images, video, and documents for AI and business insights. In this interactive LinkedIn Live chat, we're talking to Alberto Rizzoli, CEO & Co-founder of V7 Labs, a data labeling platform for text and visual data. CloudFactory and V7 regularly collaborate to optimize data labeling operations for customers and build high-quality datasets for global innovators.

Join us on November 2 at 11 am ET / 4 pm BST: Maximizing Data Labeling Operations in High-Stakes Industries: Tips for Tools and Teams

Here are a few topics we plan to discuss with V7: • Fascinating real-world examples of computer vision development in agriculture and healthcare • Maximizing data operations resources and scalability by combining SMEs like medical doctors and experienced data annotators during the AI lifecycle • Optimizing human and computer collaboration to process edge cases that baffle text annotation tools like optical character recognition (OCR) • Preparing for data annotation challenges by choosing proven tools, processes, and human in the loop workforces

Register Now

P.S. Have questions? Contact CloudFactory anytime here. You might enjoy learning about CloudFactory's collaboration with V7 on Covid-19 AI training data.

Visual Studio Code for Python and Data Science? Top 3 Plugins You Must Have by Dario Radečić via @TDataScience

Is it the best code editor for Python and Data Science?

Interesting - I had never thought of doing it that way.

8 Must-Have Git Commands for Data Scientists by @snr14 via @kdnuggets

Git is a must-have skill for data scientists. Maintaining your development work within a version control system is absolutely necessary to have a collaborative and productive working environment with your colleagues. This guide will quickly start you off in the right direction for contributing to an existing project at your organization.

I good quick reminder of the commands you need to use in Git - worth a printout or adding it to something like an Evernote folder.

WEBINAR: Gain Insights from SAP Data with Qlik and Microsoft - 28 October 2021

 

Sponsored News from Data Science Central

Webinar: Gain Insights from SAP Data with Qlik and Microsoft What: A free online webinar exclusively for IT Pros When: Thursday, October 28th, 9 AM PST / 12 PM EST Where: From the convenience of your personal computer  Register Now In this latest Data Science Central Webinar, you’ll hear how global manufacturer Greene Tweed developed an efficient, cost-effective, and logical strategy to connect Qlik Data integration and Microsoft Azure Synapse to build an intelligent supply chain for better business insight. Learn how Greene Tweed addressed their challenges and how they use data liberated from SAP for strategic analytics initiatives. In addition, you will discover: How to create a plan of attack to extract insights from massive amounts of SAP data How important change data capture is to building low latency extracts for massive data volumes Why automation with Qlik Data Integration is crucial to expedite data availability How SAP data drives insights to optimize Manufacturing & Supply Chain The gains Greene Tweed realized by moving SAP data to Azure Synapse Register today to start your journey to improving data operations, accelerating reporting, reducing systems overhead and enabling AI operations with Qlik and Azure Synapse. Speakers: Matt Hayes, VP of SAP Business, Qlik David Hufnagle, Manager, Enterprise Data and Analytics, Greene Tweed Greg Vigil, Industry Solution Director – Manufacturing, Microsoft

WEBINAR: How to build customer-oriented applications using third-party data - 28 October 2021

 

NEWSLETTER . How to build customer-oriented applications using third-party data REGISTER NOW . You’re Invited! THURSDAY, OCTOBER 28 11AM PT | 2PM ET 60 MIN SESSION REGISTER NOW Join this webinar to learn how using third-party data enhances applications to better prioritize your target customer – helping you build a more customer-centric business. In this virtual session, AWS Data Exchange will host a discussion with thought leaders from companies such as Foursquare and Nextdoor. They will share real-world examples on leveraging datasets to create a customer-centric strategy and improve business outcomes. Key takeaways include: How Nextdoor uses point-of-interest (POI) data to help improve global business data coverage and quality, discovery, verification, and onboarding experiences How Nextdoor uses POI data to improve lead generation of local businesses and grow page claim rates How to provide personalized recommendations using Amazon How to discover, find, and use third-party data with AWS Data Exchange Moderator Mohsen Malik AWS Data Team Lead, Customer Advisory Mohsen leads a team of Customer Advisors for AWS Data Exchange to help customers discover, procure, and use traditional and alternative data assets in the AWS Cloud. In this capacity, his team engages with data subscribers globally across key data domains such as location and geographic information system (GIS), consumer insights, and audience data. Mohsen’s team also works with key data providers across their data domains to reduce their operational costs and expand their customer base by leveraging cloud-native distribution. Presenters Josh Cohen Senior Vice President Product, Foursquare Previously, Josh was at Google where he was the group product manager for Publisher Advertising Platforms and Business Product Manager for Google News, responsible for global product strategy, marketing, and publisher outreach. He was also vice president of business development for the consumer media team at Reuters Media and director of business development for SmartMoney.com, a joint venture between Dow Jones and Hearst. Josh holds degrees from the University of Michigan and Columbia Business School, where he graduated Beta Gamma Sigma. Rahul Sureka Engineering Leader, Nextdoor Rahul is an Engineering Leader at Nextdoor, in charge of driving search, discovery, and marketplaces. He is a results-oriented leader with over 10 years of experience in building top-performing products. Rahul joined Nextdoor in October 2015 and led several initiatives globally to develop Nextdoor‘s first monetization platform. Rahul received a Master’s in Computer Science at University of Southern California from 2006 to 2007. Angel Goñi Oramas Enterprise Solutions Architect, AWS Angel Goñi is an Enterprise Solutions Architect at AWS. He helps enterprise customers drive their digital transformation process by leveraging AWS services. His current focus is supporting consumer packaged goods (CPG) customers with emphasis on SAP migrations to AWS. *The views and opinions of Foursquare, Nextdoor, and their presenters are their own and do not necessarily reflect the positions of AWS. About AWS Data Exchange: AWS Data Exchange makes it easy to find, subscribe to, and use third-party data in the cloud. Once subscribed to a data product, you can use the AWS Data Exchange API to load data directly into Amazon S3 and then analyze it with a wide variety of AWS analytics and machine- learning services. Click here to browse thousands of data products now available from more than 80 qualified data providers in AWS Marketplace. Visit aws.amazon.com/data-exchange to learn more. REGISTER NOW © 2021 AWS Marketplace.