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Data science

Handling Imbalanced Datasets with SMOTE in Python

Today’s post is provided by Kite Table of Contents Introduction: balanced and imbalanced datasets What is data oversampling? What is SMOTE? How does SMOTE work? SMOTE tutorial using imbalanced-learn Base model Imbalanced model SMOTE’d model Recap and conclusion Introduction: balanced and imbalanced datasets Close your eyes. Now imagine a perfect Read more…

By , 3 yearsOctober 22, 2019 ago
Data science

Data Science, the Good, the Bad, and the… Future

Today’s post is coming from Kite. Kite is a plugin for your IDE that uses machine learning to give you useful code completions for Python. You can find the original post here. Table of Contents What is data science Positives: astrophysics, biology, and sports Negatives: gender bias and more Python, Read more…

By , 3 yearsSeptember 16, 2019 ago
predicting sports outcomes
Data science

Predicting Sports Outcomes Using Python and Machine Learning

I am very happy to announce that I have released a new course on Experfy! The course covers sports prediction and betting using machine learning. I am attaching the course description below. Contact me if you are interested in a discount! Course description: Predicting sports outcomes The purpose of this Read more…

By , 5 yearsAugust 11, 2017 ago
Data science

Quick Tips: Data analysis cheat sheets

With the rapid expansion of data science and supporting technologies it can become difficult to keep up with all new developments. There is always some new library for data analysis and machine learning for R or Python. This is where cheat sheets can be a useful tool to save you Read more…

By , 5 yearsJune 21, 2017 ago
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About me
dr stylianos kampakis

Dr Stylianos (Stelios) Kampakis is a data scientist with more than 10 years of experience. He has worked with decision makers from companies of all sizes: from startups to organisations like, the US Navy, Vodafone and British Land. His work expands multiple sectors including fintech (fraud detection and valuation models), sports analytics, healtech, general AI, medical statistics, predictive maintenance and others. He has worked with many different types of technologies, from statistical models, to deep learning to blockchain and he has 2 patents pending to his name.

He has also helped many people follow a career in data science and technology.

He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School and CEO of The Tesseract Academy.

A natural polymath, with a PhD in Machine Learning and degrees in Artificial Intelligence, Statistics, Psychology, and Economics he loves using his broad skillset to solve difficult problems and help companies improve their efficiency.

The Data Scientist, 85 Great Portland St, London W1W 7LT, United Kingdom
 

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