Deep Learning From Scratch IV: Gradient Descent and Backpropagation
This is part 4 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first [...]
Deep Learning From Scratch III: Training criterion
This is part 3 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the [...]
Deep Learning From Scratch II: Perceptrons
This is part 2 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first [...]
Deep Learning From Scratch I: Computational Graphs
This is part 1 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Part I: Computational [...]
Deep Learning From Scratch: Theory and Implementation
This is a multi-part series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first part: [...]
Welcome to my blog!
Hello and welcome to my new blog! In the near future, this blog will be filled with articles about artificial intelligence, machine learning and cognitive science. I hope to see you back then! Sincerely, Daniel