Predictive Maintenance Drives Big Gains in Real World by Alex Woodie via @datanami

If you’re looking for a data project that demonstrates a clear ROI, predictive maintenance is worth a look. Delta Air Lines, for example, says predictive maintenance helped it reduce maintenance-related cancellations from 5,600 in 2010 to just 55 in 2018.

This definitely tells you of a real example of how predictive maintenance works and saves time and money for one company.

The US just released 10 principles that it hopes will make AI safer by Karen Hao via @techreview

The principles, released by the White House Office of Science and Technology Policy (OSTP), have three main goals: to ensure public engagement, limit regulatory overreach, and, most important, promote trustworthy AI that is fair, transparent, and safe. All future AI regulations will need to adhere to these principles.

Something to bear in mind when you designing anything on the AI side of things.

Google Research: Looking Back at 2019, and Forward to 2020 and Beyond by @JeffDean via @googleai

Google has a massive impact on the tools, applications and research that help steer the data science community. As with prior years, this retrospective by Jeff Dean is amazing in its scope. Includes useful summaries, screenshots, videos and linked references throughout.

This is just golden and everyone really needs to read this. You get some many ideas and learn a great deal from this too.

5 trends to expect in the new big data protection revolution by Andrea Little Limbago via @infomgmt

Instead of regurgitating many of the dominant predictions around tech buzzwords such as quantum computing, 5G, IoT, the cloud, and artificial intelligence, let’s instead focus on the inherent duality of technology.

A great article to use to compare with your own plans and strategy.

Uber Has Been Quietly Assembling One of the Most Impressive Open Source Deep Learning Stacks in the Market by @jrdothoughts via @TDataScience

A look at some of Uber’s top machine learning open source projects

Amazing the kind of things that Uber have been doing. I found this fascinating.

WEBINAR: The Beautiful Science of Data Visualization - 28 January 2020

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Data Science Central Webinar Series Event The Beautiful Science of Data Visualization Join us for this latest DSC Webinar on January 28th, 2020 Explore the scientific underpinnings of what enables people to understand data quickly and effectively. In this latest Data Science Central webinar, take a deep dive into the neuroscience of the human visual system works and learn methods for effectively telling compelling data stories. Speaker: Ashley Howard Neville, Senior Technical Evangelist -- Tableau Hosted by: Stephanie Glen, Editorial Director -- Data Science Central   Title:  The Beautiful Science of Data Visualization Date:  Tuesday, January 28th, 2020 Time:  9:00 AM - 10:00 AM PST   Space is limited so please register early: Reserve your Webinar seat now   After registering you will receive a confirmation email containing information about joining the Webinar.

Is It ‘Do-or-Die’ for AI-Driven Digital Innovation? by George Leopold via @enterprisetek

Two recent studies look at how machine learning and AI will shape the workplace of the not-so-distant future—and the consequences of not keeping up.

A great article which is a good reminder of the need to include AI and ML in your organisation if you want to catch up let alone get ahead.

New study looks at the top trends in data mining and analytics by Bob Violino via @infomgmt

Data mining can help enterprises identify anomalies, patterns, and correlations within large unstructured data sets to predict business outcomes.

I found this interesting and it gives you some pointers on things to think about including in your own plans.

WEBINAR: Weaponizing Data in the Fight Against White Collar Crimes - 21 January 2020

Data Science Central Webinar Series Event

Weaponizing Data in the Fight Against White Collar Crimes Join us for the latest DSC Webinar on January 21st, 2020 In this webinar analyst and advisor Alasdair Anderson will discuss how escalating global white collar crime activity is driving adoption of advanced analytics at a pace never before seen in mature enterprises. Organizations are having to change the way they deal with data and change the types of data that they utilize. The old data management adage of "garbage in, garbage out" has been left behind as organizations realize that agile wrangling of all data is far more valuable that static historic curated data sets. In this latest Data Science Central webinar you will learn: How large organizations are using data to fight white collar crimes The crucial role cloud technology plays in advance analytics Why data wrangling is a key functionality in dealing with "garbage" data Featured Speakers: Alasdair Anderson -- Independent Consultant Matt Derda, Customer Marketing Manager -- Trifacta Hosted by: Stephanie Glen, Editorial Director -- Data Science Central   Title:  Weaponizing Data in the Fight Against White Collar Crimes Date:  Tuesday, January 21st, 2020 Time:  2:30 PM - 3:30 PM GMT   Space is limited so please register early: Reserve your Webinar seat now   After registering you will receive a confirmation email containing information about joining the Webinar.

Soft Skills for Data Science by Rebecca Vickery via @TDataScience

To be a great data scientist, you need more than data acumen.

Some great skills to have no matter what job you do. Worth a read.

WEBINAR: State of AI Bias - 16 January 2020

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January 16, 2020 (Thursday)   10:00 AM - 10:45 AM ET     While many people believe AI can help solve complex problems plaguing modern societies, can we trust that the AI solutions directing our work and livelihood are rooted in reliable, unbiased data? Do organizations have the proper systems in place to prevent, or quickly address, issues resulting from AI bias? DataRobot surveyed more than 350 U.S. and U.K.-based CIOs, CTOs, VPs, and IT managers involved in AI and machine learning purchasing decisions to learn how AI is being used by businesses today. In this webinar Colin Priest, VP of AI Strategy at DataRobot, will share insight on: How AI is being used by businesses today Current perceptions of AI bias How to prevent AI bias efforts in the future Best, DataRobot team     Save my seat →

Why are so many AI systems named after Muppets? by James Vincent via @Verge

ELMo, BERT, Grover, Big BIRD, Rosita, RoBERTa, two ERNIEs (three if you include ERNIE 2.0), and KERMIT. It’s an inside joke that says a lot about AI development.

Until I read this I had never made the connection (not sure why) as it's obvious when you think about it.

WEBINAR: Build Machine Learning Pipelines - 15 January 2020

Live Webinar: Build Machine Learning Pipelines January 15th, 2020 @ 12pm EST Streamlining your machine learning pipeline is critical for enterprise data science to deliver better business results. Accelerating the process from data, to processing to training to deployment and back again will help you get better performing models, faster. In this webinar we'll offer solutions to the common challenges data scientists and data engineers face when building a machine learning pipeline. We will dissect each part of the pipeline and offer strategies on how to design your machine learning pipelines for a more efficient, integrated and automated process. We'll tackle ways to connect all your data sourcing in one unified location. How to create modular ML components for easy reproducibility, and automate MLOps for quick training of models and hyperparameter optimization. Streamline frequent deployment of models leveraging the power of Kubernetes. And lastly, you'll learn to design a monitoring toolkit with Grafana and Kibana for easy CI/CD. Join Solutions Architect, Aaron Schneider as he builds an end-to-end machine learning pipeline, and explains how to optimize each section for a more efficient workflow. Key webinar takeaways: Set up an efficient machine learning pipeline Learn key MLOps solutions to streamline science and engineering Create reusable ML components Build a suite of monitoring and visualization tools Instantly train and deploy ML models with Kubernetes Use CI/CD to design an auto-adaptive machine learning pipeline Unable to attend? Register for a recording of the webinar and copy of the presentation following the live stream.

Reinforcement Learning 101 by @shweta_bhatt8 via @TDataScience

The perfect place to start your reinforcement learning (RL) journey. This article covers 5 basic RL questions.

A great place to read the basics and as it says to start the journey with reinforcement learning.

10 Best and Free Machine Learning Courses, Online by Prateek Shah via @kdnuggets

Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.

You really should try some of the free courses out there - I think they will surprise you with how good they are. Then it is a case of practice, practice and practice.

WEBINAR: Ten Keys to AI Success in 2020 - 9 January 2020

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Thursday, January 09, 2020   10AM ET (45 min)     According to a recent PwC report, AI could contribute up to $15.7 trillion to the global economy by 2030. With companies around the world adopting AI at a rapid pace, we polled over 170 global enterprise customers to collect their feedback on the challenges and successes they’ve had with AI. Join this webinar to learn how industry leaders saved time and improved accuracy by using AI, resulting in reduced costs and increase overall ROI. In this webinar, you will learn: How companies strategically adopt AI across their organizations The competitive advantages early adopters of AI are gaining How companies are getting diverse teams invested in becoming AI-driven How you can choose the right use cases to ensure AI success     Register Today

WEBINAR: ML vs Holt-Winters Forecasting 14 January 2020

Data Science Central Webinar Series Event ML vs Holt-Winters Forecasting Join us for this latest DSC Webinar on January 14th, 2020 Machine Learning is all the rage, but when does it make sense to use it for forecasting? How do statistical forecasting methods compare? In this latest Data Science Central webinar, we will show you how the Holt-Winters forecasting algorithm works. Then we’ll use the HOLT_WINTERS() function with InfluxData to make our own time series forecast. Speakers: Anais Dotis-Georgiou, Developer Advocate -- InfluxData Hosted by: Rafael Knuth, Contributing Editor -- Data Science Central Title:  ML vs Holt-Winters Forecasting Date:  Tuesday, January 14th, 2020 Time:  9:00 AM - 10:00 AM PST Space is limited so please register early: Reserve your Webinar seat now