Goto

Collaborating Authors


Some Deep Learning with Python, TensorFlow and Keras

@machinelearnbot

The following problems are taken from a few assignments from the coursera course Introduction to Deep Learning (by Higher School of Economics) and Neural Networks Deep Learning (by Prof Andrew Ng, deeplearning.ai). The problem descriptions are taken straightaway from the assignments.


Implementing a Neural Network from Scratch in Python – An Introduction

#artificialintelligence

Get the code: To follow along, all the code is also available as an iPython notebook on Github. In this post we will implement a simple 3-layer neural network from scratch. We won't derive all the math that's required, but I will try to give an intuitive explanation of what we are doing. I will also point to resources for you read up on the details. Here I'm assuming that you are familiar with basic Calculus and Machine Learning concepts, e.g.


Implementing a Neural Network from Scratch in Python – an Introduction

@machinelearnbot

Get the code: To follow along, all the code is also available as an iPython notebook on Github. In this post we will implement a simple 3-layer neural network from scratch. We won't derive all the math that's required, but I will try to give an intuitive explanation of what we are doing. I will also point to resources for you read up on the details. Ideally you also know a bit about how optimization techniques like gradient descent work.


Neural Networks from Scratch (in R) – Ilia Karmanov – Medium

@machinelearnbot

This post is for those of you with a statistics/econometrics background but not necessarily a machine-learning one and for those of you who want some guidance in building a neural-network from scratch in R to better understand how everything fits (and how it doesn't).