Learning

of this series, we'll speak about deep learning. And when people speak about deep learning, we immediately consider these images of deep neural networks architectures, with many layers, neurons, and parameters. In practice, the actual...

a decade old now. Back then, OpenAI felt like one (well-baked) startup amongst others. DeepMind was already around, but not yet fully integrated into Google. And, back then, the “triad of deep learning” —...

For 18 days, we've got explored many of the core machine learning models, organized into three major families: distance- and density-based models, tree- or rule-based models, and weight-based models. Up so far, each article focused...

Even networks long considered “untrainable” can learn effectively with a little bit...

Neural Network Regressor, we now move to the classifier version. From a mathematical viewpoint, the 2 models are very similar. In truth, they differ mainly by the interpretation of the output and the selection...

are sometimes presented as black boxes. Layers, activations, gradients, backpropagation… it may feel overwhelming, especially when every thing is hidden behind model.fit(). We are going to construct a neural network regressor from scratch using Excel....

article about SVM, the subsequent natural step is Kernel SVM. At first sight, it looks like a very different model. The training happens within the dual form, we stop talking a few slope and...

we're. That is the model that motivated me, from the very starting, to make use of Excel to raised understand Machine Learning. And today, you'll see a different explanation of SVM than you normally see,...