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This 90-minute session introduces participants to the critical topic of model interpretability, focusing on feature importance using SHAP (Shapley Additive explanations).

In this 90-minute hands-on session, you’ll dive deep into creating, manipulating, and performing operations with tensors: the essential data structures behind every modern machine learning model.

Step into the world of deep learning by building your first Artificial Neural Network! In this 90-minute, beginner-friendly session,

This session will introduce you to Convolutional Neural Networks (CNNs): the deep learning architecture that powers technologies like facial recognition, autonomous vehicles, and medical image analysis.

In this 90-minute hands-on session, you’ll learn essential text preprocessing steps like tokenization, padding, and vocabulary building, and see how to turn words into numbers using embedding layers.

In this 90-minute session, you’ll learn the critical hyperparameters that control how your model learns, including optimizers, loss functions, evaluation metrics, and callbacks.

Deep learning models are data-hungry; but what if you could leverage a pre-trained network to solve your problem with much less data?

In deep learning, a model can either underfit (not learn enough from the data) or overfit (memorize the data, losing the ability to generalize).

Once you’ve built and trained your model, what’s next? You need to persist it so that it can be used later without retraining — whether that’s for evaluation, deployment, or inference on new data.