This is all about coding interesting algorithms.
What is this post about? The Rectified Linear Unit (Relu) will be beautifully dissected in this popst: https://www.youtube.com/watch?v=Un9A90mfO54 This is what you will be able to generate and understand by the end of this post. This is the evolution of a shallow Artificial Neural Network (ANN) with relu() activation functions while training. The goal is …
Dissecting Relu: A desceptively simple activation function Read More »
What will you learn? The video below, delivers the main points of this blog post on Stochastic Gradient Descent (SGD): (GitHub code available in here) https://youtu.be/gE9HzJ_GaRM In our previous 2 posts about gradient, in both post number 1 and post number 2, we did cover gradient descent in all its glory. We even went through …
Studying and Predicting the Progress of COVID-19 using Pandas and ARIMA COVID-19 has been around for nearly 4 months since the outbreak. In this notebook, we will study some of the useful statistics regarding number of confirmed/deaths/recovered cases as a function of time per each country/region. We will use the the dataset that has been …
What is Reproducibility All About? As a computer scientist, or as an academician, you do experiments with a bunch of algorithms. Let’s say you have coded a machine learning algorithm, like an Artificial Neural Network, and after doing your experiments with different datasets, you have found out that the best type of neural network has …
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 …
