AI, Machine Learning, Reinforcement Learning, and MLOps Articles

Learn more about AI, machine learning, reinforcement learning, and MLOps with our insight-packed articles. Our AI blog delves into industrial use of AI, the machine learning blog is more technical, the reinforcement learning blog is industrially renowned, and our mlops blog discusses operational ML.

Building an Enterprise NLP Platform

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Author
Photo of Dr. Phil Winder
Dr. Phil Winder
CEO

Winder.AI has built a state of the art natural language processing (NLP) platform for a large oil and gas enterprise. This work leveraged a range of cloud-native technologies and sophisticated deep learning-based (DL) machine learning (ML) techniques to deliver a range of applications. Key successes are:

  • New NLP workflows developed in hours, not weeks.
  • Hugely scalable, from zero to minimise cost to tens of thousands of concurrent connections.
  • Enforced corporate governance and unification, without burdening the developer.

Our Client

Our client, a large enterprise in the oil and gas industry, has thousands of Data Scientists working on a range of problems. This company operates throughout the world and is investing heavily in artificial intelligence (AI) to improve the entire organisation.

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Developing a Real-Life Project

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Author
Photo of Dr. Phil Winder
Dr. Phil Winder
CEO

I’m often asked questions in the vain of “how did you figure that out?”. Other times, and I’m less of a fan of these, I get questions like “you estimated X, why did it take 2*X?”, which I respond with a definition of the word estimate. Both of these types of questions are about the research and development process. Non-developers, and especially non-engineers, are often never exposed to the process of research and development. It’s highly non-linear; when it’s going well progress is rapid, but other times you get stuck after falling down a rabbit hole.

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COVID-19 Logistic Bayesian Model

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Author
Photo of Dr. Phil Winder
Dr. Phil Winder
CEO

This post builds upon the exponential model created in a previous post. The main issue was that there an exponential model does not include a limit. A logistic model introduces this limit. I also perform some very basic backtesting and future prediction.

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COVID-19 Exponential Bayesian Model

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Author
Photo of Dr. Phil Winder
Dr. Phil Winder
CEO

The purposes of this notebook is to provide initial experience with the pymc3 library for the purpose of modeling and forecasting COVID-19 virus summary statistics. This model is very simple, and therefore not very accurate, but serves as a good introduction to the topic.

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How to Start a Data Science Project With No or Little Data

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Author
Photo of Hajar Khizou
Hajar Khizou
Associate Data Science Content Editor

Data is an essential asset of modern business. It empowers companies by surfacing unique insights about their customers and creates actionable products. The more data you possess, the better you meet and exceed your customers’ expectations.

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Keep it Clean: Why Bad Data Ruins Projects and How to Fix it

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Author
Photo of Dr. Phil Winder
Dr. Phil Winder
CEO


Slides

Abstract

The Internet is full of examples of how to train models. But the reality is that industrial projects spend the majority of the time working with data. The largest improvements in performance can often be found through improving the underlying data.

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