This is all about coding interesting algorithms.
What will you Learn in this Post? Neural Networks are function approximators. For example, in a supervised learning setting, given loads of inputs and loads of outputs in our training data, a neural network is capable of finding the hidden mapping between the those inputs and outputs. It can also, hopefully, generalize its acquired knowledge …
Train a Perceptron to Learn the AND Gate from Scratch in Python Read More »
Hello friends and welcome to MLDawn! So what sometimes concerns me is the fact that magnificent packages such as PyTorch (indeed amazing), TensorFlow (indeed a nightmare), and Keras (indeed great), have prevented machine learning enthusiasts to really learn the science behind how the machine learns. To be more accurate, there is nothing wrong with having …
Hello friends and welcome to MLDawn! So what sometimes concerns me is the fact that magnificent packages such as PyTorch (indeed amazing), TensorFlow (indeed a nightmare), and Keras (indeed great), have prevented machine learning enthusiasts to really learn the science behind how the machine learns. To be more accurate, there is nothing wrong with having …