Online education has certainly gone mainstream. Developers and companies have finally gotten comfortable taking online courses. Sometimes these are recorded, self-paced courses like we have at Talk Python Training. Other times, they are more like live events in webcast format.
Open source has permeated much of the software industry. What about health care? This highly regulated and important industry might seem to be the domain of huge specialized software companies.
You might use Python every day. But how much do you know about what happens under the covers, down at the C level? When you type something like variable = [], what are the byte-codes that accomplish this? How about the class backing the list itself?
In this episode, we'll dive into one of the foundations of modern data science, Bayesian algorithms, and thinking. Join me along with guest Max Sklar as we look at the algorithmic side of data science.
Collaborative data science has a few challenges. First of all, those who you are collaborating with might not be savvy enough in the computer science techniques (for example, git and source control or docker and Linux). Second, seeing the work and changes others have made is a challenge too. That's …
Let's start with a philosophical question: Are you human? Are you sure? We could begin to answer the question physically. Are you made up of cells that would typically be considered as belonging to the human body?
Do you do data science? Imagine you work with over 200 data scientists. Many of whom have diverse backgrounds or have come from non-CS backgrounds. Some of them want to use Python. Others are keen to work with R.
Do you dream of a day when you can write Python in the browser rather than JavaScript? This is no pipe dream! There are several ways to write Python that runs in the browser already.
Have you heard of awesome lists? They are well, pretty awesome! Gathering up the most loved libraries and packages for a given topic.
Folks, it's not like the old days where there were just a couple of web frameworks for building apps with Python. These days there are many. One of those frameworks is the Masonite web framework created by Joseph Mancuso. Joseph is here today to tell us all about Masonite, what …
When you think about the types of jobs you get as a Python developer, you probably weight the differences between data science and web development.
Have you ever wanted to get into consulting? Maybe you're seeking the freedom to work on whatever project you'd like or gain more control of your time.
You've often heard me talk about Python as a superpower. It can amplify whatever you're interested in or what you have specialized in for your career. This episode is an amazing example of this. You'll meet Cornelis van Lit. He is a scholar of medieval Islamic philosophy and woks at …
On this episode, we dive into Python for lawyers and a special tool for conducting legal interviews. Imagine you have to collect details for 20,000 participants in a class-action lawsuit. docassemble, a sweet Python web app, can do it for you with easy.
What's it's like building a startup with Python and going through a tech accelerator? You're about to find out. On this episode, you'll meet Elissa Shevinsky from Faster Than Light. They are building a static code analysis as a service business for Python and other code bases. We touch on …
Did you come to software development outside of traditional computer science? This is common, and even how I got into programming myself. I think it's especially true for data science and scientific computing. That's why I'm thrilled to bring you an episode with Daniel Chen about maintainable data science tips …
If you're a data scientist, how do you deliver your analysis and your models to the people who need them? A really good option is to serve them over Flask as an API. But there are some special considerations you might keep in mind. How should you structure this API? …
Have you heard that Python is not good for writing concurrent asynchronous code? This is generally a misconception. But there is one class of parallel computing that Python is not good at: CPU bound work running the Python layer.
Have you heard that Python is not good for writing concurrent asynchronous code? This is generally a misconception. But there is one class of parallel computing that Python is not good at: CPU bound work running the Python layer. What's the main problem? It's Python's GIL or Global Interpreter Lock …
Back in May of 2018, Bob Belderbos, Julian Sequeira, and I started on what would be a 9-month project. We wanted to create a dedicated, 100 days of code course specifically for Python web developers. Much of what we created for that course, we had prior experience with. But much …