WEBINAR: The New Era of Actionable Intelligence - 8 September 2021

 

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Webinar: The New Era of Actionable Intelligence What: A free online webinar exclusively for IT Pros When: Wednesday, September 8th, 9 AM PST / 12 PM EST Where: From the convenience of your personal computer  Register Now Cloud enablement is changing where and how you can deliver insights. AI- and ML-based augmented features are making BI accessible to more users.  In this webinar, join Doug Henschen, Principal Analyst at Constellation Research; and Denise LaForgia, Director of Product Marketing at Qlik, to learn: How SaaS and hybrid cloud deployment options can drive consistent-yet-flexible deployment across on-premises and private and public cloud data centers How natural language understanding and machine-learning-based analysis features are simplifying the use of BI for all users Why concise embedding at the point of decision is a crucial step toward in-the-moment awareness of your business and immediate decision making Click here to reserve your spot!

Python loops: A comprehensive guide by Mahbubul Alam via @TDataScience

 Looping over lists, tuples, dictionaries & strings and loop control — break, continue, pass.

This is very clear and he gives some code snippets to help you understand how to do FOR and WHILE loops in Python. A useful guide to save somewhere to refer back to when you need a quick reminder.

The one data platform to rule them all… but according to whom? by/via @LM_Braswell

Great post that breaks down a lot of the recent startups and organizes them by popular end users (e.g. data scientist, analyst, ML engineer, etc). Since a lot of the data tooling startups eventually want to become "data platforms," this post makes it easy to understand where they all fit. 

A great article. Subscribe to her newsletter - you know it makes sense.

The Difference Between Data Scientists and ML Engineers by Kurtis Pykes via @kdnuggets

What's the difference? Responsibilities, expertise, and salary expectations.

I like that this gives some places to get training as well as clear expectation on salary.

WEBINAR: Building Smart Health Wearables - August

 

Webinar Series Click Here to Register Title: Building Smart Health Wearables Date: Tuesday, Aug 31, 2021 Time: 9:00 am PDT / 4:00 pm UTC Duration: 60 minutes   SUMMARY Deploying machine learning on embedded devices with scarce resources is one of the most exciting developments of the past years, enabling smarter and more efficient IoT devices. Edge Impulse and Texas Instruments have partnered to combine best in class IoT microcontrollers and sensor hardware with the Edge Impulse embedded machine learning platform. Join us for a hands-on tutorial on building a wearable fall detection device using the TI CC1352P LaunchPad and the Edge Impulse platform. Collect live data, design a neural network, and deploy it to an embedded device with no prior machine learning experience required. Speakers: David Schwarz, User Success Engineer at Edge Impulse Mark Easley, TI University Program Marketing Manager at Texas Instruments   Click Here to Register

Data doesn't speak for itself: Why data storytelling is so important by/via @YellowfinBI

“Letting the data speak for itself” is a well-known phrase with a hard truth: Data presented on its own rarely communicates meaning for itself. For most people, it’s the context behind the numbers, the story, that helps us understand and care to act.

This is so true - you have to try and tell a story with the data that you find and analyse if you want to communicate it adequately to others - if you don't do that then you have failed and it was almost a waste of time to look at it to start with. We all need to tell the story well enough that we bring those reading it with us - get them to believe and be invested in what you are saying. We can all learn from sales techniques when it comes to selling a vision with data.

AI Doesn’t Have to Be Too Complicated or Expensive for Your Business by Andrew Ng via @HarvardBiz

For companies that are interested in using AI but don't have access to vast troves of data, there hasn't been a clear path to follow. But because of that, those industries may be the best-untapped opportunities for AI. In this article, Andrew Ng takes a look at the issues, the opportunities, and why now is the time to get started.

A good piece and a great explanation of how a small and simple use of AI could give you a great benefit that doesn't have to cost the earth. We all know, sometimes it is good to do a project with a quick win in order to gain confidence in technology as well as the ability of the department's ability to deliver.

WEBINAR: Using third-party healthcare data to accelerate drug discovery and clinical trial protocol design - 27 August 2021

 

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NEWSLETTER . Using third-party healthcare data to accelerate drug discovery and clinical trial protocol design REGISTER NOW . You’re Invited! FRIDAY, AUGUST 27 11AM PT | 2PM ET 60 MIN SESSION REGISTER NOW Join this webinar to learn how to leverage external healthcare datasets to make faster decisions with greater accuracy – accelerating biomedical development and improving patient welfare. In this virtual session, AWS Data Exchange will host a panel discussion with thought-leaders from healthcare powerhouse companies like QIAGEN and IBM Watson Health. Learn about the critical role third-party datasets have played in the evolution of the healthcare and life sciences industry. Key takeaways include: Incorporating QIAGEN molecular and genomics data into the biomedical research and development process Re-designing clinical trials to maximize patient and provider enrollment of patients with IBM Watson Health data Extracting more meaningful insights from your healthcare data by leveraging machine-learning algorithms Streamlining the integration, access, and analysis of diverse datasets by utilizing AWS Data Exchange Moderator Fred Lee, MD, MPH Healthcare & Life Sciences Leader, AWS Data Exchange Dr. Lee provides physician leadership for AWS Data Exchange where he is focused on transforming and disrupting the exchange of healthcare and life sciences data towards a cloud-native, socially responsible, economically sustainable, and privacy-preserving state. Fred brings a broad range of professional experience to this role, having served as a practicing academic physician, a health system executive, founder of a precision medicine startup, an industry market strategy executive, and as an industry leader for precision medicine and real-world evidence in the healthcare and life sciences sectors. Fred is a member of the American Medical Informatics Association and is an Industry Advisory Board appointee for the Cancer Informatics Society. He received his MD from Stony Brook School of Medicine, his MPH from the Columbia Mailman School of Public Health, and is a licensed physician in the state of New York, with a clinical background in general surgery and preventive medicine. Presenters Matt Newman, PhD Vice President of Business Development and Professional Services, QIAGEN Matt Newman is the Vice President of Business Development & Professional Services at QIAGEN Digital Insight, specializing in partnerships for bioinformatics software and data solutions, as well as helping to lead the QIAGEN Digital Insights Professional Services organization. Before joining QIAGEN, Matt helped to form OmicSoft Corporation, specializing in software and data services for the analysis of genomic datasets. OmicSoft Corporation was acquired In January 2017. Prior to OmicSoft, Matt worked in the lab at Glaxo Smith Kline, utilizing skills learned with a BS from Penn State University. Luke Boulanger, MA, MBA Lead Offering Manager for MarketScan Databases, IBM Watson Health Luke Boulanger is an academically trained health economist, specializing in health economics and outcomes research for approximately 25 years and focuses on the design, implementation, and dissemination of real-world observational studies. Leveraging his extensive experience in several therapeutic areas, Luke directs hybrid and retrospective studies, analyzing and synthesizing clinical and economic data from a wide variety of sources. Luke has authored over 45 peer-reviewed publications in journals like Diabetes Care, COPD, HIV Medicine, Annals of Pharmacotherapy, and Neurology and is currently a PhD candidate in economics. Kanchan Waikar Senior Solutions Architect, AWS Kanchan Waikar is a Senior Solutions Architect for the AWS Marketplace for Machine Learning team with over 14 years of experience building, architecting, and managing NLP and software development projects. With a Master of Science in Computer Science, Kanchan uses her passion for data science to help customers harness the power of machine learning to build more effective AWS architectures *The views and opinions of QIAGEN and IBM Watson Health and their presenters are their own and do not necessarily reflect the positions of AWS

3 Reasons Why You Should Use Linear Regression Models Instead of Neural Networks by Terence Shin via @kdnuggets

While there may always seem to be something new, cool, and shiny in the field of AI/ML, classic statistical methods that leverage machine learning techniques remain powerful and practical for solving many real-world business problems.

Some really good points in this article that make sense if you think about it a bit more. I particularly like point #2 as anything that makes it easier to communicate with others definitely gets my vote.

WEBINAR: Visual Analytics Design - for Perception and Inference - 24 August 2021

 

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Webinar: Visual Analytics Design - for Perception and Inference What: A free online webinar exclusively for IT Pros When: Tuesday, August 24th, 9 AM PST / 12 PM EST Where: From the convenience of your personal computer  Register Now Register to attend a lively conversation about visual design in this latest Data Science Central webinar. Dr. Spotfire Representative Neil Kanungo is joined by TIBCO Chief Analytics Officer Michael O’Connell for a discussion on visual design best practices and the science behind visual perception. They discuss the importance of accuracy and cognitive speed in human perception, and how to design visual applications to avoid subjective bias and illusion. You will come away with a greater understanding of visual analytics communication and tips to improve your own work.

7 Cool Python Packages Kagglers Are Using Without Telling You by Bekhruz Tuychiev via @TDataScience

Bex T reveals the secrets.

We can all definitely use these and it should help our code be much faster and efficient too. Definitely work a bookmark - I already added it to my own Evernote library so I can refer back to it.

Data science isn’t your only career option by Natassha Selvaraj via @TDataScience

A breakdown of high paying data related careers in 2021.

I think many of us can think about our own jobs and realise that we actually fit into one of the jobs outlined at a high level by Natassha - probably a Data Engineer for me (although I was mostly known as a Data Architect). Don't be blinkered into thinking you need the sexy Data Scientist job title.

Try these more detailed definitions: 

Data Engineer

Data Architect

Data Scientist

Machine Learning Engineer

WEBINAR: Wrangle the Data Abyss: Build, Test, & Deliver - 19 August 2021

 

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Webinar: Wrangle the Data Abyss: Build, Test, & Deliver What: A free online webinar exclusively for IT Pros When: Thursday, August 19th, 9 AM PST / 12 PM EST Where: From the convenience of your personal computer  Register Now Register to attend a lively conversation about data visualization in this latest Data Science Central webinar. The hardest part of being an analyst isn’t building the dashboard, it is getting the data in a state where you can gain insights. In this webinar, you will learn how to efficiently build, test and deliver a thoughtful analysis. We will dive deep to uncover the nuanced process of building a dataset and dashboard that will be fully utilized. Click here to reserve your spot!

Python Data Structures Compared by Matthew Mayo via @kdnuggets

Let's take a look at 5 different Python data structures and see how they could be used to store data we might be processing in our everyday tasks, as well as the relative memory they use for storage and time they take to create and access. 

This is very useful if you need a primer or reminder of the differences between them. Very useful.

11 Python Tricks to Boost Your Python Skills Significantly by Görkem Arslan via @PY_PlainEnglish

 

You won’t believe how much easier things will become in Python with these tricks!

This is VERY useful and needs to be bookmarked or printing and kept on the wall to refer back to. Incredibly useful.

WEBINAR: From Connected Factory to Connected Machine: How IIoT Can Elevate Your Manufacturing Business Strategy - 17 August 2021

 

Webinar Series Click Here to Register Title: From Connected Factory to Connected Machine: How IIoT Can Elevate Your Manufacturing Business Strategy Date: Tuesday, August 17, 2021 Time: 8:00 am PDT/ 3:00 pm UTC Duration: 60 minutes   SUMMARY What could you do with an extra 104.1 seconds per cycle? What if you could identify failures 10.5 hours in advance? How would your business benefit if you could identify inefficiencies 85% faster? The Industrial Internet of Things (IIoT) is revolutionizing manufacturing, with the global IoT connected machines market projected to reach $1.3 trillion by 2027. At the core, sensors are enabling connections throughout the value chain—from people to machines to data—providing complete, real-time operational visibility that is improving decision making, efficiency, quality and creating new service opportunities.  IIoT is the most transformative technology of the decade, but ensuring reliable, secure data collection with remote access can be difficult. Moreover, when you’re trying to manage your devices and apps for your industrial IoT solution, writing custom code to solve all the challenges you face is complicated, time-consuming and costly. Join this webinar to learn:  How to transform your machines into profit centers What options exist to enable connected machines and boost productivity and efficiency How to quickly connect the factory to the enterprise Speaker: Ricardo Stefanato Buranello, Head of Platforms Business Unit, Telit   Click Here to Register

7 Amazing Python One-Liners You Must Know by Pranjal Saxena via @TDateScience

Speedup pandas, quick data profiling, data scraping, and many more.

These are very useful and I did not know all of them. Worth a read and a potential bookmark.

WEBINAR: Wrangle the Data Abyss: Build, Test, & Deliver - 19 August 2021

 

Data Science Central Webinar Series Event

Wrangle the Data Abyss: Build, Test, & Deliver Join us for this latest DSC Webinar on August 19th, 2021 The hardest part of being an analyst isn’t building the dashboard, it is getting the data in a state where you can gain insights. Data is always messy, in many different places, and often different platforms making the back end work take up the majority of the time to create a dashboard. We will dive deep to uncover the nuanced process of building a dataset and dashboard that will be fully utilized! In this latest Data Science Central webinar, you will learn how to efficiently build, test and deliver a thoughtful analysis. Speaker:   Lauren Alexander, Senior Marketing Analyst - Tableau   Hosted by:   Sean Welch, Host and Producer- Data Science Central   Title:  Wrangle the Data Abyss: Build, Test, & Deliver Date:  Wednesday, August 19th, 2021 Time:  9:00 AM - 10:00 AM PST   Space is limited so please register early: Reserve your seat now