Machine learning is undoubtedly one of the hottest topics in software development right now. And for good reason. Machine learning opens up a whole world of new possibilities for developers, exciting app owners and end users alike. From greater personalisation to smarter recommendations, improved search functions, intelligent assistants, and applications that can see, hear, and react – machine learning can improve an app and the experience of using it in all manner of ways.

Blockchain is conceivably one of the most disruptive technologies that have recently appeared on the tech scene. You'll find Blockchain at the core of Bitcoin and other cryptocurrencies that have enjoyed the spotlight for the last few years. But you will also find it in finance, Internet of Things applications, healthcare, and even government.

Python has rapidly increased in popularity in recent years and is now one of the most widely used programming languages in the world. If you are considering using it for your next web development project, then you may also be aware of Python’s emerging rivalry with a younger language, Go.

Python is so good that, instead of describing what it can do, it’s actually faster to say what Python can’t do. Python is good for a little bit of everything.

Django is a popular back-end framework for building Python web apps. It can be used to develop complex websites with vast databases, and it promotes fast software development that’s perfect for high-velocity web projects. Many companies chose Django for just these reasons, including Instagram, The Washington Times, and Mozilla. So what’s the secret to Django’s high development speed? Find out how to estimate development speed and lower the costs of building your Django app.

Python has enjoyed a steady rise to fame over recent years and is now jostling for the position of one of the most popular programming languages in the world. Favoured for applications ranging from web development to scripting and process automation, Python is quickly becoming the top choice among developers for artificial intelligence (AI), machine learning, and deep learning projects.

Python is a programming language that has been around for quite a while now and has become very popular. However, it seemed like it wasn’t as much in the spotlight as some of the other languages, despite being used by Google. In reality, Python developers weren’t a hot commodity because the language itself wasn’t used widely as some of the others, such as JavaScript, Java, C, or C++.

Two programming languages probably couldn’t be more different from each other than Python and PHP. The former is hailed for its simplicity and straightforwardness, while the latter is often criticized for its quirks and tendency to generate spaghetti-like codebases. Python brings to mind modern applications such as machine learning and data science, while PHP is mostly associated with old-timey web development and old-school discussion forums. Still, both remain popular and have their benefits and disadvantages. In this blogpost, we’ll try to present a fair comparison of Python and PHP, taking into account a number of factors which you should consider when choosing the language for your new software project.

Let’s say that you’re at the very beginning of developing your app. Equipped with a solid business plan, you decide to go with Python, and you’re betting on the Django framework, ready to make the first decisions that will take this project from concept to reality. One of the most fundamental things to do at this stage is to find a Django-friendly hosting service.

For many years, R has been the obvious choice for those going into data science. In recent years, something’s changed, however, and R got dethroned. How is Python challenging R’s well-established position and why is Python the king of data science now?