10,000 levels of Candy Crush Saga and 2 trillion gameplays: What does King do with all this data?
A few ways King has invested in Data Science to create enduring fun player experiences.
Blog Archives
Introduction to deep learning NLP
Introduction to deep learning NLP by Paola Puglisi & Louise Kirkham Nowadays many organisations deal with huge amounts of text data, such as customers review, tweets, newsletters, emails, etc. Natural Language Processing is the art of extracting useful information from these new data sources. During this hour we’ll first give you a brief introduction to […]
Introduction to reinforcement learning with Atari Games
Introduction to reinforcement learning with Atari Games by Daniel Cook March 2016, AlphaGo beats Lee Sedol. Reinforcement learning, so hot right now! Baffled by the Bellman equation and gradient backpropagation, I had to sit through a Data Science degree to get to the bottom of it. Why does everyone prefer to explain things with maths […]
Intro to Computer Vision
Intro to Computer Vision by Chanuki Seresinhe The introduction of convolutional neural networks (CNNs) has led to dramatic improvements in computer vision tasks. Data scientists might hesitate to use CNNs in their own work, as deep learning models tend to require vast quantities of training data to create useful models. However, transfer learning is a […]
Intro to Natural Language Processing
Intro to Natural Language Processing by Partha Dey “Hey Siri”, “Ok Google”, “Alexa…” – how do machines understand us and how does it all happen so fast; in this session, we’ll go from the building blocks of how NLP works and how devices that you use every day work.
Introduction to Machine Learning: Clustering
Introduction to Machine Learning: Clustering by Ethan Soo & Rashid Muhamedrahimov This Introduction to Machine Learning session will look at clustering, a type of unsupervised learning: learning about the relationships within your data when you do not have any labels. You will learn about two main types of algorithm: k-means clustering and hierarchical clustering. We […]
Introduction to Machine Learning – Classification
Introduction to Machine Learning – Classification by Rashid Muhamedrahimov & Enrico Alemani This Introduction to Machine Learning session will look at clustering, a type of unsupervised learning: learning about the relationships within your data when you do not have any labels. You will learn about two main types of algorithm: k-means clustering and hierarchical clustering. […]
Introduction to Machine Learning: Regression
Introduction to Machine Learning: Regression This Introduction to Machine Learning session will look at regression: estimating relationships and predicting outcomes when the target variable is continuous. You will learn the basic concepts of regression and will be introduced to some of the algorithms, techniques to measure and evaluate the relationship between variables, and some of […]
Introduction to Python Libraries and Algorithms for Machine Learning
Introduction to Python Libraries and Algorithms for Machine Learning by Luke Menzies This session aims to give an introduction to machine learning implementation for Python, using key libraries. This introduction will also include a brief introduction to the key logic used under the hood of these libraries, in order to implement machine learning methods such […]