In this post we will discuss a way of representing a state that has exciting connections with how our brain seems to work. First, we’ll briefly look at some foundational ideas (representation and generalisation). Next, we’ll introduce the Successor Representation (SR), which is motivated by finding a representation that generalises across states, and that might be useful in reinforcement learning. … Read More
Using generators in Python to train machine learning models
If you want to train a machine learning model on a large dataset such as ImageNet, especially if you want to use GPUs, you’ll need to think about how you can stay within your GPU or CPU’s memory limits. Generators are a great way of doing this in Python. What is a generator? A generator is a function that behaves … Read More
How to run scripts in the background
When running machine learning experiments, you might want to run multiple scripts simultaneously, hide printouts for a script or just do things in a terminal window while running a Jupyter Notebook in the background. In this post, we will go through how to run scripts in the background, bring them back to the foreground, and check if the scripts are … Read More
Using Bash Scripts to Parallelise Data Preprocessing for Machine Learning Experiments
Parallelising data preprocessing can save you a lot of time. In this post, we’ll go through how to use bash scripts to make parallelising computation easier. The idea is that you split up the data you need to preprocess into different batches, and you run a few batches on each machine. The bash scripts help you loop through batches to … Read More