Author: Vincent Granville
Ajit’s research is focused on Data Science for IoT. He teaches the same at Oxford University and UPM in Madrid (@forumoxford + @citysciences). Ajit is also launching a course / certification in Data Sciences for Industrial IoT. His personal research interests include Deep Learning algorithms for IoT/future city domains.
The selection below features some of his recent articles:
- Tutorial – foundations of ML and data science for developers
- Data Science for IoT vs Classic Data Science: 10 Differences
- Enterprise AI insights from the AI Europe event in London
- Twelve types of Artificial Intelligence (AI) problems
- Data readiness strategies of AI Start-ups
- Book review: The Mathematical Corporation
- Behavioural Biometrics, IoT and AI
- Non-traditional strategies for mid-career switch to #Datascience and #AI
- Enterprise AI: Learning from the evolution of Robotic Process Automaton
- IOTA – The potential to drive Data Science for IoT
- In 2018 – AI will start to bring jobs back from offshore destinations to the West
- GDPR and AI – strategies and options in a nutshell
- Data Science for IoT – The Big Picture
- How you can stay up to date with your #AI and #ML knowledge
- Four Quadrants of the Enterprise AI business case
- Can we use deliberate practise for learning to code #AI and #ML
- Solving problems with DataScience for Internet of Things
- The applications of AI in the Telecoms industry
- Re-thinking Enterprise business processes using Augmented Intelligence
- How to create an #Enterprise #AI Business case driven by Data
- How to use IoT datasets in #AI applications (full stack)
- Landing a 150k USD #datascientist job – Seven things you need to know
- AI and Algorithmocracy: What the Future Will Look Like
- MBA vs. Data Science qualifications – Does #AI and #DataScience explain the fall in MBA applications?
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