A collaborative and supportive community at the University of Gloucestershire for students interested in machine learning and deep neural networks.
Learn MoreThe University of Gloucestershire Machine Learning Society is a community dedicated to exploring the fascinating world of neural networks and deep learning. We provide a supportive environment where students can learn, collaborate, and discover their passion within this rapidly evolving field.
Our bi-weekly sessions cover topics ranging from the fundamentals of neural networks to advanced concepts in transformers, RNNs, CNNs, and practical skills like effective prompting.
Whether you're just beginning your journey in machine learning or looking to deepen your expertise, our society offers resources, mentorship, and a network of like-minded individuals who share your curiosity and enthusiasm.
Join Our CommunityThe fundamental building blocks of neural networks, perceptrons are inspired by biological neurons. They take multiple inputs, apply weights, and produce an output through an activation function.
This hyperparameter controls how much a model changes in response to error. Too high, and the model may overshoot; too low, and training becomes inefficient.
Loss functions measure the difference between predictions and actual values. By minimizing loss, neural networks improve their accuracy.
The algorithm that powers neural network learning, backpropagation calculates gradients of the loss with respect to weights.
Non-linear activations like ReLU, sigmoid, and tanh allow neural networks to learn complex patterns.
Try the Linear Classifier Lab. Compare the classic Perceptron with Logistic Regression on simple 2D datasets, or draw your own points.
Launch Linear Classifier LabReady to explore the fascinating world of neural networks and deep learning? Join our community of like-minded students and researchers at the University of Gloucestershire.
We meet every two weeks for sessions covering various aspects of machine learning, from basic concepts to advanced topics. No prior experience is necessary, just bring your curiosity!
Official Society Page: uogsu.com/society/16083/
Discord Community: discord.gg/HKd9QjF5Vz