Success with the IoT starts with understanding 'Thing Management' by Timothy Chou via @infomgmt

Most organizations think of asset management as the practice of tracking and managing IT devices such as routers, switches, laptops and smartphones. But that’s now only part of the picture.

Great opinion piece by Timothy that gives some great examples and good advice.

Build your own Robust Deep Learning Environment in Minutes by Dipanjan (DJ) Sarkar via @Medium

You have many options for configuring a GPU-enabled training environment in the cloud. This article details some of them and describes minimal configuration cloud-based deep learning environment providers (Google Colaboratory, Paperspace Gradient°, Lambda GPU Cloud, AWS Deep Learning AMIs, etc.) that give you point-and-click access to the environment.

I found this really interesting and it was great to have it explained so clearly.

WEBINAR; Predictive Analytics: Practical Applications 4th April 2019

Data Science Central Webinar Series Event

Predictive Analytics: Practical Applications Join us for the latest DSC Webinar on April 4th, 2019 From optimizing processes to increasing revenue and driving business growth, executives are realizing the value in artificial intelligence. However, many organizations struggle to bring the necessary people, processes, and technology stacks together. In this latest Data Science Central webinar, we’ll focus on the business processes needed to implement AI-driven insights within an organization. We will discuss: Investments in new platforms and roles for your strategic roadmap End-to-end business-focused delivery strategy good for the whole team Facilitating change with the right tools and people Attend to hear real ROI use cases of an end-to-end AI rollout in retail and the financial services industry and some of the successes and setbacks along the way. It's time to empower everyone to solve anything. Speakers: Razvan Nistor, Chief Data Scientist -- Keyrus Melissa Burroughs, Product Manager -- Alteryx Hosted by: Stephanie Glen, Editorial Director -- Data Science Central   Title:  Predictive Analytics: Practical Applications Date:  Thursday, April 4th, 2019 Time:  9 AM - 10 AM PDT   Space is limited so please register early: Reserve your Webinar seat now

9 Artificial Intelligence Trends You Should Keep An Eye On In 2019 by Tyler Durden via zerohedge

Artificial Intelligence has become a hot topic in tech circles. It has not only changed our lives, but it has also disrupted every industry you can think of.

I found this an interesting article and thought it was worth a share.

SLIDESHOW: 7 emerging data security and risk management trends by David Weldon via @infomgmt

Risk appetite statements, governance frameworks and password-less authentication are among the growing trends that will impact security, privacy and risk leaders, says Gartner.

Some good observations that are definitely worth thinking about.

10 Git Commands You Should Know by @discdiver via @Medium

Understanding these commands and their common flags can save you a lot of time. This article covers a range of commands from inspecting changes and undoing to escaping Vim.

Some of these are really useful and this article is well worth a bookmark and some applause.

Close to half of startups jump on the AI bandwagon without the tech by @SecurityCharlie via @ZDNet

According to a report by MMC Ventures, close to 40% of European companies claiming to use AI don’t actually use it, with 1 in 12 EU startups claiming to be an AI-focused company. It may be because startups claiming to develop AI raise more capital through investment rounds than software firms without AI. Or it could just be that people are still misusing the term AI.

I think it has always been the case that new technology terms have been misunderstood, or used for purposes to get funding. I think there needs to be better clarity and understanding of terms as it feels very dishonest to be using something as amazing as AI to get kudos or funding when it is not actually being used.

WEBINAR: Patterns For Successful Data Science Projects - 14 March 2019

Patterns For Successful Data Science Projects Join us for the latest DSC Webinar on March 14th, 2019 Running data science workloads is a challenge regardless of whether you are running them on your laptop, on an on-premises cluster, or in the cloud. While buying 100% managed service is an option, these tools can be expensive and lack extensibility. Therefore, many companies opt for open source data science tools like scikit-learn and Apache Spark’s MLlib in order to balance both functionality and cost. However, even if a project succeeds at a point in time with any set of tools, these projects become harder and harder to maintain as data volumes increase and a desire for real-time pushes technology to its limit. New projects also struggle as new challenges of scale invalidate previous assumptions. In this latest Data Science Central Webinar, we will discuss some patterns we see that companies leverage to succeed with their data science projects. Key takeaways will be: Strategies for removing cognitive load for you and your team How to execute a program that is simple and effective How to best use the ecosystem of tools to be successful Speaker: Bill Chambers, Data Scientist -- Databricks Hosted by: Rafael Knuth, Contributing Editor -- Data Science Central Title:  Patterns For Successful Data Science Projects Date:  Thursday, March 14th, 2019 Time:  09:00 AM - 10:00 AM PDT Space is limited so please register early: Reserve your Webinar seat now

Democratisation: The future of data management, with caveats by Rohit Mahajan via @infomgmt

Tracking, correlating and putting all of the data to good use requires a firm commitment to technologies such as AI and machine learning for both smart data discovery and cataloguing purposes.

Good article by Rohit which I found very interesting and worth reading and reminding yourself.

WEBINAR: Advanced Mapping With Tableau - 13 March 2019

Advanced Mapping With Tableau Join us for this latest DSC Webinar on March 13th, 2019 Every dataset contains a “Where” component. For organizations that need to use location to drive their business, it is critical that they can unlock the Where in their data. In this latest Data Science Central webinar, find out how Tableau can help you work with spatial data and answer location-based questions. This webinar will cover several topics, including: Connecting and joining data to common spatial data sources in Tableau, like Shapefiles and SQL Server Different ways to look at the spatial distribution of data Using advanced operations to understand spatial relationships and spatially aggregate your data Examples of interaction-based analysis and exploration Options integrating with ArcGIS Maps and providing the right context for geospatial analysis Speaker: Kent Marten, Staff Product Manager, Maps and Spatial Analysis -- Tableau Hosted by: Stephanie Glen, Editorial Director -- Data Science Central   Title:  Advanced Mapping With Tableau Date:  Wednesday, March 13th, 2019 Time:  9:00 AM - 10:00 AM PDT   Space is limited so please register early: Reserve your Webinar seat now

How investors use AI and ML to gain an edge By Matt Egan via @CNNI

“We’re not crazy pointed-hair scientists,” said Mike Chen, an equity portfolio manager at PanAgora, but they do use AI.

I like this article and I know it is going to move more in that way going forward. Other companies also used technology like that for example the newer Digital Wealth Managers like Nutmeg for example who I personally use for investments with great results.

WEBINAR: Making AI Work in the Real World - 12 March 2019

Making AI Work in the Real World Join us for this latest DSC Webinar on March 12th, 2019 If you’ve read your fair share of tech press, you’ve certainly been exposed to breathless forecasts about the promise and power of artificial intelligence. The thing is, a lot of those articles are light on detail or focus too heavily on algorithms and not on business value. In this latest Data Science Central webinar, Alyssa Simpson Rochwerger of Figure Eight takes an industry-by-industry perspective on true AI adoption. We will cover: An approach to AI that realizes business value Real-world examples of businesses using AI to improve their bottom line Real-world use cases in e-commerce, enterprise software, robotics & IoT, AgTech, and more We will separate the hype from the reality, the theoretical from the practical, and the research labs from ROI. Speaker: Alyssa Simpson Rochwerger, VP of Product -- Figure Eight Hosted by: Steve Miller, Editorial Contributor and Moderator -- Data Science Central   Title:  Making AI Work in the Real World Date:  Tuesday, March 12th, 2019 Time:  9:00 AM - 10:00 AM PDT

Register here

OpenAI’s new multitalented AI writes, translates, and slanders by James Vincent via @verge

OpenAI is said to have trained an unsupervised language model that can read and write at a level that's never been seen before. It's called GPT-2 and they say it's so good, they're afraid to release it. This article in The Verge explores the claims and the presumed dangers, including samples of GPT-2's capabilities. Follow the links for more info, code and related articles.

I really liked this article which was a great read and definitely made me think about it.