machine learning 🛳️ The Titanic: Predicting Survival I have been working A LOT with Fast.ai lately, and I am loving it. I am learning so many new approaches that I feel like get overlooked by many in the field when discussions arise. But I have to admit: I was a little nervous when it came to
neural networks 🐸 CIFAR10 with Fast.ai I had a project where I was meant to get the highest accuracy possible on this set with PyTorch, no convolution, no pooling, not even a learning rate scheduler, just linear neural networks. Ask me how frustrating that was! The highest I could get was 52%, after HOURS and HOURS
fast.ai 👗 Fashion MNIST vs. Fast.ai First of all, I really like working with this dataset, but it is not without its issues. For example, I, being a human of high intelligence and mental capacity, look at some of the shirts vs t-shirts vs pullovers vs coats vs dresses, and there are MANY of them that
neural networks 🔥 Hot or Not? Beauty in the Eye of the Mainstream I know it sounds a bit callous, but hear me out. After I made my first three little web apps using fast.ai neural network methods, for classifying cats vs dogs, 3 different types of bears, and 3 human emotions/facial expressions, I watched my children spend literally HOURS playing
