Every once in a while, I have the pleasure of hosting an article on this blog that truly rocks my world. This is one of them.
Any new domain can be daunting at first, no matter the opportunities it offers. Machine learning is no exception.
Which is why nothing is more valuable than having a ready-to-go template to making your first steps in a new and exciting field.
Two of our Expert Python Developers, Radosław Jankiewicz and Tomasz Maćkowiak, have prepared everything you need to get started. If you’re looking for a practical introduction to machine learning in Python ...
When you’re thinking about hosting your app, you want it to be as hassle-free as possible.
After all, you’re on your way to create software that will transform your organization, your community - possibly the world. (No need for modesty here!)
On that path to greatness, there’s no room for hosting frustrations.
Everyone wishes for a hosting solution that makes it easy to deploy features rapidly. It should also be cost-effective, keeping your bottom line happy and freeing up resources to put towards development.
That’s exactly the reason we’d like to tell you about Serverless.
Artificial Intelligence can compose songs, paint pictures, help in cancer therapy, drive cars and play games. It’s also starting to write code. Does it mean that the days of human developers are already numbered?
Articles praising the usage of unit testing are a dime a dozen. A little less popular but still readily available are articles that will try to convince you that unit tests are a waste of time, at least in some cases.
Most of them (or maybe even all?) try to prove their arguments based on feelings, on the author’s own assessment of what is good and effective or bad and inefficient.
In this article, I won’t be trying to prove which side is right.
Go (often referred to as golang) is awesome!
Let me explain why a Python fan of many years could say that. But to understand that we have to go back in time to see how my fascination with Python began.
In fintech, you can’t afford to fly blind.
This is especially true for your choice of tech stack. You don’t want to fall behind the competition due to lack of proper research.
Or maybe you’re just plain curious about the top solutions for fintech companies. Python is a great choice in this industry - but which companies use it, specifically?
We’ve got you covered with our list of top 15 fintechs that use Python in their tech stack.
At some point in the creation of your fintech start-up you will have to make decisions that are very hard to un-make. One such decision is your choice of tech stack. If you go wrong here, your costs may skyrocket down the line, putting you in the red despite best intentions.
Your fintech needs a programming language that is easy to handle, scalable, mature, high-performance and coupled with ready-made libraries and components.
Luckily, Python is there to deliver it all. Read on and you’ll find that it’s quite easy to make a case for Python in this industry.
STX Next’s Python developers are set to continue the company’s mission of spreading effective coding practices by speaking at two Python conferences in the coming weeks, EuroPython and PyParis.
Being a free, cross-platform, general-purpose and high-level programming language, Python has been widely adopted by the scientific community. Scientists value Python for its precise and efficient syntax, relatively flat learning curve and the fact that it integrates well with other languages (e.g. C/C++). As a result of this popularity there are plenty of Python scientific packages for data visualization, machine learning, natural language processing, complex data analysis and more. Here’s our list of the most popular Python scientific libraries and tools.
When you outsource the development of your product, communication is key. Otherwise, you may find yourself with under-performing software that no one is happy with. Let’s go over how the right communication may help you get what you paid for - bespoke software tailored to your needs.