WEBINAR: Drive Greater Business Outcomes with AI and Machine Learning 5 November 2020

 

Drive Greater Business Outcomes with AI and Machine Learning November 5th, 2020 | 1:00 pm EST - 60 min including Q&A Register Now Symphony Care Network provides post-acute long-term care, and for them, reduced patient readmissions are key to improving patient care and reducing healthcare costs. In this webinar, hear how Symphony's small analytics team was able to process vast amounts of patient data, build multiple automated data science models concurrently, evaluate the models and deploy a working readmission machine learning (ML) model in hours. The increase in productivity allowed the team to tackle additional data science projects, and the company gained key insights about the readmission process. Discover how DataRobot on Amazon Web Services (AWS) helps you leverage Artificial Intelligence (AI) with end-to-end automation for building, deploying, and managing ML models. In this webinar, you'll learn to: Seamlessly prepare data-including Amazon Redshift data-for machine learning modeling Deliver AI and ML at scale and continuously optimize performance Answer complex business questions and make accurate forecasts-regardless of team size Register Now

WEBINAR: How to Stop Worrying and Start Tackling AI Bias - 12 November 2020

 

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The stories of bias in AI are everywhere: Amazon’s recruiting tool, Apple’s credit card limits, Google’s facial recognition, and dozens more. The quick solution is just to blame the algorithm and its designers. But it’s not a question of whether or not you have bias in your institution, but rather how you plan to handle it. We will explore the answers that question and many more in our webinar, How to Stop Worrying and Start Tackling AI Bias, where we will cover: Reframing the conversation around AI and understanding it as the first step in building a more ethical, fairer system How machine learning can highlight the implicit bias of an institution and how AI is a new toolset to measure and change it A practical plan that you can implement to improve your AI development and increase trust in your AI Register now

Logging Like a Pro by Neal Hu via @ITNEXT_io

Theories and best practices on effective application logging.

I think logging is critical and a log is just as much a piece of data worthy of reporting against as something containing customer or order information. This is the place where you get clues about what is wrong with the system, where you find out who deleted what, and conversely who added what. 

Another option is to also add a flag to every record in a file that signifies if it was added, updated or deleted. Then you don't lose data. Think about that combined with a log to capture the update details.

WEBINAR: How to Drive Python Model ROI & User Engagement - 11 November 2020

 

Data Science Central Webinar Series Event

How to Drive Python Model ROI & User Engagement Join us for this latest DSC Webinar on November 11th, 2020 Python is one of the most popular modeling languages in the world, and yet more than half of the time, developers fail to deliver their advanced analytics to the business end-user. The main barrier is the lack of a deployment platform that converts models into user-friendly applications. Instead of having to continue running these models yourself or relying on a patchwork of open-source platforms, we’d like to (re-) introduce you to an enterprise-ready solution that fully integrates with Python to convert your analytics into a useable, interactable form: FICO Xpress Insight. If you work with Python, don’t miss this chance to learn how to overcome all of the "last-mile” obstacles and actually generate applications that allow for what-if analyses, reporting, user management, load balancing, drag-and-drop UI creation capabilities, and more. In today’s Data Science Central webinar, we’ll show you: How to deploy a Python model in FICO Xpress Insight in 5 minutes Customization options for Python models Practical demonstrations of several common use cases Finally, data scientists and operations researchers can stop wasting time, money, and effort on advanced analytics that never get put to use—be sure to join us! In today’s Data Science Central webinar, we’ll show you: Speakers: Dr. Oliver Bastert, Vice President of Product Management - FICO Dr. Johannes Mueller, Senior Optimization Modeler - FICO Dr. Vladimir Roitch, Senior Scientist - FICO Hosted by: Bill Vorhies, Editorial Contributor - Data Science Central   Title:  How to Drive Python Model ROI & User Engagement Date:  Wednesday, November 11th, 2020 Time:  9:00 AM - 10:00 AM PDT   Space is limited so please register early: Reserve your Webinar seat now

A step-by-step guide for creating an authentic data science portfolio project by Felix Vemmer in @kdnuggets

Especially if you are starting out launching yourself as a Data Scientist, you will want to first demonstrate your skills through interesting data science project ideas that you can implement and share. This step-by-step guide shows you how to do go through this process, with an original example that explores Germany’s biggest frequent flyer forum, Vielfliegertreff.

This is a great roadmap into what you need to do, what you need to create and document, what you should share and a great suggestion on where to share it. I would also suggest adding it to Kaggle as the site Felix suggest is German and a little niche.

CONFERENCE: AI Experience EMEA Virtual Conference - 10 November 2020

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Did you know that 84% of organizations find they can’t fully trust deployed models to make accurate predictions? It falls upon data and analytics leaders like you to ensure AI initiatives are still relevant and adding value to the business.  As AI transforms business and society, delivering value quickly, reducing costs and risks, and becoming more competitive are the name of the game. Join us for a FREE, one-day virtual conference to learn how your business can be more agile, more accurate, and more strategic in its decision-making. Conference attendees will: Get valuable advice on how to address hyper-critical issues impacting your organization today Hear about AI-driven use cases from pioneers in your industry and how they are solving pressing business problems Gain practical insights on how to create your AI strategy and scale your organization’s success with AI Over 1,000 attendees | 20+ speakers with experience in AI Success | All sessions available on demand Register Now

22 Pythonic Tricks for Working with Strings by @ra_quinn via @Medium

String manipulation is something we Pythonistas do a lot. Here are 20 top tips & tricks you might find useful.

This is definitely worth a read if for nothing but reminding yourself of all the methods that you probably know but have forgotten.

25 Useless Code Comments People Actually Wrote In Their Code. by @tunvir_rahman via @JS_PlainEnglish

We are all stuck inside, so you might as well read this - besides you might recognise some that you have done yourself. I certainly did lol

I think over time we all get better at commenting in code - my advice is stick to facts and something that is useful - not long-winded paragraphs of descriptions.

The Ultimate Python Guide for Beginners by @DijkhuizenBryan via @TDataScience

 Some of the fundamentals of the programming language by Bryan Dijkhuizen.

This is a useful and short guide which is interesting if you are wondering if you should give it a try.

Data Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science by Benjamin Obi Tayo Ph.D. via @TDataScience

Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.

This is a great shopping list and you can find free courses on the various MOOCs if you need to fill a gap in your knowledge. Certainly, I had to do a set of maths and statistics courses on Coursera to get myself up to a required level. Never give up - if something is difficult, find a free online course and plug that gap in your knowledge.

Top 29 Useful Python Snippets That Save You Time by @MikhailRaevskiy from @thestartup_

 Here are his favourite 29 Python code snippets that actually save time as a developer.

These are really useful and I can think of lots of ways in which these would have made code more efficient or the results better.  Just be careful - I personally don't agree with ignoring a false value - you need to investigate why you received it in the first place and what caused it. You could lose an important link back to a system of record if you lose it.

Microsoft And Shell Announce New Partnership To Use Artificial Intelligence And Tech To Reduce Carbon Emissions by @BernardMarr via @forbes

 Tackling carbon emissions is one of the biggest challenges faced by the world today. For big business, this means making a strategic and managed move towards increasing the use of renewable energy sources, as well as creating efficiencies across all aspects of their operations.

This is a great initiative and I wish them every success.  As expected a great article from Bernard.

WEBINAR: Industrialized ML for Governed, Responsible and Explainable AI - 20 October 2020

 

Sponsored News from Data Science Central   October 20         10am PDT Hi, Despite the $42 billion in funding for ML applications and platforms, scaling and operating ML applications remains challenging.  Join the October 20 webinar to learn how Accenture’s industry-based, reusable production ML workflows fit seamlessly with Databricks’ Unified Data Analytics Platform to enable data teams to operationalize machine learning at scale.  Using this model, hear how Navy Federal Credit Union leveraged industrialized ML, scaling its capabilities to deliver next generation member service. You’ll also leave understanding how to bake model quality, compliance, responsible AI and explainable AI into all your production models. SAVE MY SEAT

WEBINAR: The Last Mile to AI ROI - 15 October 2020

 

While you have hired top-notch data scientists to build models and invested in data science tools, your AI projects still may not be getting off the ground. Research shows that the share of AI models deemed "production worthy" but never put into production is anywhere between 50 and 90%. Do you see yourself on that spectrum? So, what are leaders and teams actually missing? What can they do to finally gain value out of AI? The last mile for AI initiative success is the deployment and management of models in production that require new practices, skills, and technologies. This emerging area is called Machine Learning Operations, or MLOps, also referred to as ModelOps by leading analyst firms. MLOps solves precisely for this challenge by bridging the gap between data and IT Ops teams, providing the capabilities that both teams need to work together to deploy, monitor, manage, and govern machine learning models in production. In this webinar, we provide insights into what MLOps is and how any organization can adopt it to finally derive value from machine learning projects. During this session, you will learn: How to eliminate AI-related risks by adopting MLOps best practices The inherent challenges of production model deployment and how to overcome them Model monitoring best practices What production lifecycle management is and why it matters Register now

Making Python Programs Blazingly Fast by @Martin_Heinz_ in @TDataScience

 Let’s look at the performance of our Python programs and see how to make them up to 30% faster!

Some great tips and lots of code examples too.

9 Free Programming Courses by Harvard, MIT, IBM, Google, and Microsoft by/via @dottedSquirrel

 And get optionally certified for the price of your groceries. 

This is definitely something worth investigating if this is the career path you want to take.

What are Python Iterators and Generators? Programming Concepts Every Data Science Professional Should Know by Aniruddha Bhandari via @AnalyticsVidhya

 Let’s learn about looping techniques using functions like enumerate, zip, sorted, reversed in python.

I love this article which will help you to handle large amounts of data in Python. 

WEBINAR: Scale ML Innovation on AWS with Kubeflow and SageMaker 7 October 2020

 

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OCTOBER 7 | 11 AM PT | 2 PM ET Join Provectus and AWS as we explain how to build an end-to-end infrastructure for machine learning using Kubeflow and SageMaker, and show why MLOps and reproducible ML are key to enabling the delivery of ML-driven innovation at scale that results in: Faster time to market of ML-based solutions More rapid rate of experimentation and innovation Assurance of quality, trustworthiness, and ethical AI At the webinar, we will also discuss what goes into building such fundamental components of ML infrastructure as a reusable feature store, reproducible experimentation and model training pipelines, CI/CD for MLOps, and production monitoring and model re-training. This webinar is ideal for IT decision-makers, data scientists, and DevOps engineers. It is illustrated with real-world case studies. RESERVE YOUR SEAT Can’t make it to the webinar? Register anyway anyway to receive a link to the recorded session once it’s available.

4 SQL Tips for Data Scientists and Data Engineers by @SeattleDataGuy via @BttrProgramming

 Please, don’t average averages is the first tip he has for us. 

These are really valuable insights and I completely agree with his observations. I love that he has given you code segments as well so there are no excuses for not understanding these.  Some of these links seamlessly into basic rules of data analytics and make sure that you do not skew your results.

WEBINAR: Reporting Made Easy: 3 Steps to a Stronger KPI Strategy 7 October 2020

 

Data Science Central Webinar Series Event Reporting Made Easy: 3 Steps to a Stronger KPI Strategy Join us for this latest DSC Webinar on October 7th, 2020 Are people across your business capturing metrics – but can’t say exactly why? Are KPIs poured into reports, but too few are understood? When KPIs do get discussed, do they rarely lead to changes in direction? Each of these is a sign that your current KPIs aren’t paying off. In a data-driven world, finding your way to successful KPIs requires the right strategy. Join us for this latest Data Science Central webinar and we’ll help you get there. Qlik® Head of Data Literacy, Jordan Morrow, and author Bernard Marr, will reveal how to: Select the KPIs that matter most to your business Report, evolve and refine your KPIs on a schedule Create a KPI-driven culture and boost data literacy across all your teams Speakers: Jordan Morrow,Global Head of Data Literacy -Qlik Bernard Marr,Best-selling author, Futurist, Strategic Advisor - Bernard Marr & Co Hosted by: Sean Welch, Host and Producer -- Data Science Central   Title:  Reporting Made Easy: 3 Steps to a Stronger KPI Strategy Date:  Wednesday, October 7th, 2020 Time:  9:00 AM - 10:00 AM PDT   Space is limited so please register early: Reserve your Webinar seat now