The graph represents a network of 4,865 Twitter users whose tweets in the requested range contained "digitaltransformation", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 23 November 2022 at 13:06 UTC. The requested start date was Wednesday, 23 November 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 19-day, 8-hour, 39-minute period from Thursday, 03 November 2022 at 16:21 UTC to Wednesday, 23 November 2022 at 01:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

Imagine a world in which deep learning takes over from established data science methods. In this world, it's not just algorithms that learn – the entire system does! The field is still maturing, and the underlying math can be challenging to understand. Still, prominent data scientists can now run their programs on neural networks without worrying about how they work. This blog article will teach you how to use deep learning in your data science work.

The graph represents a network of 4,130 Twitter users whose tweets in the requested range contained "digitaltransformation", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 17 August 2022 at 12:04 UTC. The requested start date was Wednesday, 17 August 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 1-hour, 0-minute period from Sunday, 14 August 2022 at 23:00 UTC to Wednesday, 17 August 2022 at 00:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

The graph represents a network of 4,090 Twitter users whose tweets in the requested range contained "digitaltransformation", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 08 June 2022 at 12:06 UTC. The requested start date was Wednesday, 08 June 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 7-hour, 41-minute period from Sunday, 05 June 2022 at 16:19 UTC to Wednesday, 08 June 2022 at 00:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

Blockchain accelerates the adoption of emerging technologies, including Artificial Intelligence, Cloud, and IoT, by bringing in the missing element of trust required for a business to embrace these technologies at scale fully. In the next side, blockchain business networks benefit from integrating these technologies into modern blockchain platforms and applications. Blockchain and Artificial Intelligence will stand in reshaping industries. Both technologies came with immense benefits and brought their challenges for adoption. It is also fair that the hype surrounding these technologies may be unprecedented, so some may view the thought of getting these two ingredients together as brewing a modern-day version of IT pixie dust. Simultaneously, there is a logical way to think about this mash-up that is both sensible and pragmatic.

According to Gartner, By 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated. Real data is any data that is produced or obtained through direct measurement, typically sensors in a manufacturing environment. This data is often constrained by cost, logistics, and privacy. In fact, sometimes real data can be downright dangerous to collect! Imagine an application where you need car crash data – Too expensive and risky to get real data.

In this episode of SaugaTalks, hosted by Irene Lyakovetsky, I met Stu Bailey, Co-founder and Chief Enterprise AI Architect at ModelOp, to discuss why #ModelOps is a Critical Piece of Enterprise AI Strategy. It is not surprising seeing why #ModelOps is the cornerstone of every #AI initiative. Technology Talk Host: SaugaTalks Chats With Fascinating People In Tech! Follow: bit.ly/SaugaTalksLI and Subscribe For The Full Episodes: bit.ly/SaugaTalks "#ModelOps is a Key #Enterprise Capability for End-to-end #Governance of #AI Initiatives Across the Organization" #SaugaTalks with Giuliano Liguori, Digital Transformation Leader, Innovation Manager, Thought Leader, Board Member CIO Club IT and Stu Bailey, Co-founder and Chief Enterprise AI Architect at ModelOp Full Episode: https://lnkd.in/eVAxm_mt

The graph represents a network of 4,243 Twitter users whose tweets in the requested range contained "digitaltransformation", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 17 November 2021 at 13:18 UTC. The requested start date was Wednesday, 17 November 2021 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 16-hour, 48-minute period from Sunday, 14 November 2021 at 08:12 UTC to Wednesday, 17 November 2021 at 01:01 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

Welcome to the May 2021 edition of '10 Important Technology And Innovation Tweets'. The tweets are mostly listed in chronological order. Tweet 01 ℹ #DigitalTransformation in #ITSM seems like a natural development, but if you're thinking #CloudNative, there are some things to focus on. Here are some guides to download: https://t.co/MyMeJ1RnFC An autonomous robot uses AI and lasers to keep fields herbicide free!

The graph represents a network of 4,567 Twitter users whose tweets in the requested range contained "digitaltransformation", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 10 November 2021 at 13:19 UTC. The requested start date was Wednesday, 10 November 2021 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 4-hour, 41-minute period from Sunday, 07 November 2021 at 20:19 UTC to Wednesday, 10 November 2021 at 01:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.