It is Thursday morning in the Twin Cities of Minneapolis and St. Paul. Even though we are still officially in summer, the highs and lows for the days are going down. Hopefully we will have at least two more months of decent weather to walk outside.
As I mentioned in the last posts, we are going to start solving problems in Python. According to the PYPL Index, for results collected in August 2021, the most popular programming language is Python with a share of 31.47%. Java is second with a 19.14% share.
According to the IEEE Spectrum article “Top Programming Languages 2021 Python dominates as the de facto platform for new technologies” Python is number 1. I guess it is time to start solving problems in Python. In our next post I will start solving easy problems. We will then progress to medium and hard.
As you might already know, I like to refresh on tools I will be using. I decided to start watching “Introduction to Python Fundamentals: Lesson 01” by Paul Deitel published by Pearson Education, Inc. Since I am a member of the ACM (https://en.wikipedia.org/wiki/Association_for_Computing_Machinery) I have access to O’Reilly titles. If you work developing software, I strongly recommend you joining the ACM. They provide a wealth of information at your fingertips. For example, earlier today I attended the webinar “Quantum Computational Supremacy” by Scott Aaronson. I do not work with quantum computers, but enjoy learning about the technology. If you have a chance, watch the recording of the webinar which should be available in a few days.
Continue reading “Introduction to Python Fundamentals – Lesson 1”
It is Friday afternoon and we are still observing social distancing restrictions and working from home. That said, things are slowly relaxing and more people are out and about. The number of cars on the road has more than tripled since the stay home order started a couple months ago. Please observer social distancing and wear a mask when in public. It is for your well being, your family and friends, your country, and all human beings on this planet.
It is Wednesday in the Twin Cities of Minneapolis and St. Paul. My wife and I spent most of the morning dealing with health insurance. Hopefully all will be done in the next few days. I am in the process of changing health insurance companies. Due to the COVID-19 pandemic everyone is using some type of video application to communicate. The proposed application was 
A couple weeks ago one of my wife’s nice told her that there is a Costco store in Minneapolis that seems to sell different items and in larger packages than others. The 
It is Thursday April 23, 2020 and in the Twin Cities of Minneapolis and St. Paul we are still in lockdown for the COVID-19 pandemic, but with some eased restrictions. The Federal Government has defined a very specific set of steps to gradually lift the quarantine in the country. Now it is up to the different States to apply the rules as they fit. If there is a recurrence then the state MUST go back to square one (full quarantine) and repeat the process somewhat slower in order not to overtax the healthcare system. 
In a 
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. 
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. 
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.