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Article originally posted on Data Science Central. Visit Data Science Central
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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