Building a machine learning model isn’t just about finding the right algorithm—it’s about the right process. In Machine Learning in Production, Andrew Ng breaks down the iterative loop of model development: training, error analysis, refining hyperparameters, and improving data. Getting to a high test set accuracy is one thing, but aligning your model with real-world business metrics? That’s where the real challenge begins. Learn how to bridge the gap between models and impact: https://hubs.la/Q0

Deep learning is all about depth—literally! While logistic regression and single-layer neural networks are considered ‘shallow,’ multi-layer architectures unlock the ability to learn complex functions that shallow models can’t. Learn the fundamentals and build your understanding of deep neural networks in the Deep Learning Specialization by Andrew Ng: https://hubs.la/Q02-X2f60 | DeepLearning.AI