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”

Broadcasting in Numpy

Broadcasting is a feature of Python and Numpy. When one is performing array operations, in some cases the shapes of the arguments do not match. The good and bad thing is that Python assumes what you want to happen and does it. In most cases the results are fine, but on occasions Python might do something that you are not expecting. This post discusses to some degree what is broadcasting. The idea is that we will be using it in a future post when doing some regressions for image recognition. Continue reading “Broadcasting in Numpy”

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”

Numpy Vectorization

As you may already know, I have been taking several AI / ML related courses. I am a firm believer in always keep on learning. Some time ago I read a report about people in the USA reading books. The statistic that called my attention was:  42% of college graduates never read another book after college. That seems to me quite disturbing. Another statistic is:  57% of new books are not read to completion. To this indicates that a) readers are not committed to learning and / or books are getting worse. Continue reading “Numpy Vectorization”

Using Docker – Installation

If you follow me on Twitter (@john_canessa) you have noticed that in the past couple months or so I have been posting tweets regarding articles in Medium. The site is geared to creating posts which you could do using your own web site (e.g., www.johncanessa.com). The beauty is that many talented individuals in different fields are posting there. The site organizes them by categories and presents the articles indicating the estimated reading time. One of these days I will probably start posting there. Continue reading “Using Docker – Installation”