What is machine learning?
Have you heard of machine learning before? Did you try to figure out what machine learning is? Are you struggling to start? This article will discuss what machine learning is; …
Course: Applied Data Science
The future of data science
You have learned the core skills in data science as you have progressed through this course. Data science as a discipline is relatively young, and continues to evolve as existing …
Precision and recall
At this point in the course, you have successfully built your first model to classify portrait and landscape paintings based on their physical dimensions. Now we must ask ourselves how …
The data science lifecycle
Now that we have got to know our tools, let’s learn a bit about the general process of Data Science, in other words, how and when we might apply these …
What is data science and how do we use data?
Welcome to the introductory course in applied data science. You have joined the course because you are interested in learning more about data science, and some of the fundamentals of …
Social data
So far in this course, you have learned how to use largely tabular data, usually in the form of a Comma-Separated File (CSV). However, not all data comes in the …
Working with data APIs
This week we will learn how to analyse and visualise social media data. The activities will be more practical than theoretical, but we will take you through the steps and …
Data Science Resources
There is a wealth of reliable information on the topic of data science. Although we do not necessarily endorse the resources listed below, we have listed some of our favourites …
Data Science: How do Neural Networks Work?
A neural network is a set of algorithms that aims to recognise the relationships in a set of data by mimicking the way that the human brain works. The basic …
Welcome back
Welcome to the second week of Applied Data Science. Last week we learned about fundamental data science topics, including how to explore the data with basic data analytics tools and …
The curse of dimensionality: organising data in high-dimensional spaces
Have you ever tried to explain a complex topic or discuss the information and different characteristics of a dataset with a friend and somewhere in the middle you were struggling …
Feature extraction
By introducing the concept of dimensionality reduction, we realise the importance of feature selection for data analytics. However, which features are the best to select for our model? That is …
Classification and clustering
In order to improve our artwork model, we are now going to combine the ratio and title models using the ideas introduced in the previous step. In order to do …
Your model and the truth
We have built three different models for our Tate dataset to figure out how we can, in general, determine whether a painting is a landscape, a portrait, or some other …
Review of the week
This week you have learned the basics of data science work. We took a simple data set from the Tate Modern composed of information about paintings, and demonstrated the process …