Logistic Regression with a Neural Network mindset

It is a very snowy day in the Twin Cities of Minneapolis and St. Paul. Schools are closed due to the amount of snow and low visibility. It started snowing earlier this morning and according to forecast, it should end around 09:00 PM this evening. We have already surpassed the snow amount for February according to records that go back over a century. We will be receiving more snow in the upcoming days. Will see if we set other new records.

In this post I will cover a logistic regression implementation used to determine if pictures contain a cat or not. The code is based on an edited assignment for Coursera Neural Networks and Deep Learning. Continue reading “Logistic Regression with a Neural Network mindset”

Python Basics with Numpy

In a previous post I commented on waking up exactly at 05:00 AM. This morning I woke up around 04:10 AM. I guess there is some variation every day on how much sleep you get based on several factors (i.e., physical exhaustion, mental exhaustion, noise, temperature, food intake, among others). Continue reading “Python Basics with Numpy”

Numpy Vector Notes for Machine Learning

When learning and working with Python on machine learning it is important to make sure that Numpy arrays have the proper dimensions. Using improper dimensions may cause issues / bugs that are hard to track yet it is simple to prevent and we will see in this post. Continue reading “Numpy Vector Notes for Machine Learning”

Numpy Vectorization – Revisited

It is the last Sunday in January 2019 and is relatively cold in the Twin Cities of Minneapolis and St. Paul. The computerized mercury scale indicates -12F not taking into account wind. As usual, get up before 05:00 AM and get in my first 2 hour block of Deep Work. I am in the process of reviewing the last course I took on neural networks and deep learning. Continue reading “Numpy Vectorization – Revisited”