Thomas Wood

verfied profile

I am a freelance Consultant Data Scientist working for my company Fast Data Science.

I help organisations extract value from unstructured data with AI and machine learning. I specialise in text (natural language processing), images, and healthcare/pharmaceuticals.

If an organisation has large volumes of text data, incoming emails to triage, insurance reports, legal or scientific documents, I am the right person to leverage machine learning to extract useful information from the materials.

Career

I originally studied Physics to Masters level at the University of Durham, UK. I moved into the machine learning field in 2007, completing a second Masters in Computer Speech, Text and Internet Technology at the University of Cambridge in 2008.

Since then I have stayed in the exciting field of machine learning for more than 10 years. I have worked in a variety of companies in industries including consulting, pharmaceuticals, computer science, recruitment, retail and security, as well as some research experience.

Since 2018 I have been working as a freelance data scientist consultant, helping large organisations around the globe extract value from unstructured data such as text and images.

You can see information about me personally here.

Precision and Recall

Precision can be measured as of the total actual positive cases, how many positives were predicted correctly. It can be represented as: Precision = TP / (TP + FP) Whereas recall is described as the measured of how many of the positive predictions were correct It can be represented as: Recall = TP / (TP + FN)

Classifier Harmonic Mean Probability
08/11/2020 ∙ 265 ∙ share

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Generative Adversarial Network

A generative adversarial network (GAN) is an unsupervised machine learning architecture that trains two neural networks by forcing them to “outwit” each other.

Classifier Estimator (Statistics) Autoencoder
07/22/2020 ∙ 1162 ∙ share

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Transformer Neural Network

The transformer is a component used in many neural network designs that takes an input in the form of a sequence of vectors, and converts it into a vector called an encoding, and then decodes it back into another sequence.

Supervised Learning Tensorflow Neural Network
07/07/2020 ∙ 88 ∙ share

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Convolutional Neural Network

A convolutional neural network, or CNN, is a deep learning neural network designed for processing structured arrays of data such as images.

ImageNet Classifier Estimator (Statistics)
05/17/2019 ∙ 1200 ∙ share

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F-Score

The F score, also called the F1 score or F measure, is a measure of a test’s accuracy.

Machine Learning Harmonic Mean Geometric Mean
05/17/2019 ∙ 611 ∙ share

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Softmax Function

The softmax function is a function that turns a vector of K real values into a vector of K real values that sum to 1. The input values can be positive, negative, zero, or greater than one, but the softmax transforms them into values between 0 and 1, so that they can be interpreted as probabilities.

Vector Classifier Confusion Matrix
05/17/2019 ∙ 172 ∙ share

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Thomas Wood

Precision and Recall

Generative Adversarial Network

Transformer Neural Network

Convolutional Neural Network

F-Score

Softmax Function