Logistic regression as a neural network
As a teacher of Data Science (Data Science for Internet of Things course at the University of Oxford), I am always fascinated in cross connection… Read More »Logistic regression as a neural network
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ajitjaokar
Based in London, Ajit's work spans research, entrepreneurship, and academia relating to artificial intelligence (AI) with Cyber-Physical systems. He is the course director of the course: Artificial Intelligence: Cloud and Edge Implementations at the University of Oxford. He is also a visiting fellow in Engineering Sciences at the University of Oxford. Besides this, he also conducts the University of Oxford courses: Digital Twins, Cybseecurity, and Agtech. Ajit works as a Data Scientist through his company, feynlabs - focusing on building innovative early-stage AI prototypes for complex AI applications. Besides the University of Oxford, Ajit has also conducted AI courses at the London School of Economics (LSE), Universidad Politécnica de Madrid (UPM), and as part of The Future Society at the Harvard Kennedy School of Government.
Correlation does not equal causation but How exactly do you determine causation?
Introduction Co-relation does not equal causation – is a mantra drilled into a Data Scientist from an early age That’s fine .. But very few… Read More »Correlation does not equal causation but How exactly do you determine causation?
TensorFlow 1.x vs 2.x. – summary of changes
Overview of changes TensorFlow 1.0 vs TensorFlow 2.0 Earlier this year, Google announced TensorFlow 2.0, it is a major leap from the existing TensorFlow 1.0.… Read More »TensorFlow 1.x vs 2.x. – summary of changes
Explaining Logistic Regression as Generalized Linear Model (in use as a classifier)
The explanation of Logistic Regression as a Generalized Linear Model and use as a classifier is often confusing. In this article, I try to explain… Read More »Explaining Logistic Regression as Generalized Linear Model (in use as a classifier)
IoT – where are the stream analytics use cases?
I have been looking at this problem over a few years now The IoT industry often speaks of handling both high volumes and high throughputs… Read More »IoT – where are the stream analytics use cases?
“Will china dominate AI?” – is the wrong question
Introduction Will china dominate AI? When I spoke at the UK China business forum last month, I discussed this topic in response to an audience… Read More »“Will china dominate AI?” – is the wrong question
Can an ethical and algorithmically transparent cloud kitchen prevent future Amazon fires?
Can an ethical and algorithmically transparent cloud kitchen prevent future Amazon fires? We often view AI with suspicion – but AI can be used to… Read More »Can an ethical and algorithmically transparent cloud kitchen prevent future Amazon fires?
The AI Edge Engineer: Extending the power of CI/CD to Edge devices using containers
The AI Edge Engineer: Extending the power of CI/CD to Edge devices using containers Background At the Artificial Intelligence – Cloud and Edge implementations course… Read More »The AI Edge Engineer: Extending the power of CI/CD to Edge devices using containers
Three-way data splits (training, test and validation) for model selection and performance estimation
The use of training, validation and test datasets is common but not easily understood. In this post, I attempt to clarify this concept. The post… Read More »Three-way data splits (training, test and validation) for model selection and performance estimation
Free book – Containerize your Apps with Docker and Kubernetes and impact of containers for AI on Edge devices
Background Containerize your Apps with Docker and Kubernetes is an excellent free book from Gabriel N. Schenker You can download the whole book by registering… Read More »Free book – Containerize your Apps with Docker and Kubernetes and impact of containers for AI on Edge devices