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AI and the big data revolution have already made a huge impact in sectors such as retail, healthcare, education, and autonomous driving. Now, manufacturing is experiencing rapid transformation thanks to a combination of AI and advanced technologies like the Internet of Things.
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Python is one of the best and most popular programming languages on the technology market. Thanks to its power and versatility, it can be used for a range of applications – from simple scripts, to data analysis, to machine learning (ML). Which is why in 2018, we decided to include both Python and ML in our core tech stack at Netguru. During this intense year, we have grown our Python team to 11 experienced developers and built a number of applications using the language. Some examples include:
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At Netguru we create beautiful software for clients from all over the world. However, it’s not everything that we do in here. Every once in a while we have an idea, concept or simply we want to challenge ourselves in a creative and meaningful way. By doing so we’re able to create awesome things like Car Lens - ML project. We still want more!
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How to Design Offline-first Approach in a Mobile App

Nowadays, almost everyone uses WiFi at home, workplace, or even when commuting. When there is no wireless network available, we connect to the mobile network. Does it mean that we shouldn't be concerned with the availability of network when making mobile apps? Not really. There are many scenarios where a short period of no connectivity can ruin your app’s "smoothness".
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In order to create easily maintainable websites, a lot of companies decide to use content management systems (CMS). This way a lot of features like adding content, authorizing, and administration can be easily taken care of without a lot of programming knowledge. There are a lot of CMSs and they vary a lot, but most of them share the same idea of giving the user the ability to manage his website the easiest way possible. The most popular CMSs are created in PHP and one of them is Drupal, the third-most popular system. It is mostly used to create knowledge bases and business blogs. However, if we look at the recent popularity of programming languages, we can easily notice that Python is gaining more and more popularity and PHP is going the other way. In this case, we will take a look at three Python-based CMSs and compare them with Drupal and see what comes of it.
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Python frameworks can be divided into a few areas as Python is a very diverse language and can be used in various fields. Each of these fields has its own frameworks, some of which are more popular than others. One of the most popular fields Python is applied in is web development, which we will focus on today.
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7 Python and Django Performance Optimization Tips

In the world of app development, performance optimization is a never-ending, yet necessary, job. One that can be fairly rewarding - and not only in terms of developers’ personal satisfaction... First and foremost, better performance very often leads to higher conversion and user retention rates, which is directly connected with profit gains.
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How Python is Used in Finance and Fintech

Common in applications that range from risk management to cryptocurrencies, Python has become one of the most popular programming languages among financial institutions and fintechs. Its simplicity and robust modeling capabilities make it an excellent tool for researchers, analysts, and traders.
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Access to capital? Naaah. Corporate tax rates? No biggie. The biggest concern facing the C-suite is finding access to skilled software developers and engineers.
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Machine learning is one of the hottest topics in the world of technology. It makes sense then that so many companies are analysing whether they can benefit from it. Should you decide to enhance your business with ML, the question of finding a suitable team will arise immediately. Which is better: building an in-house machine learning team or outsourcing your needs to an industry specialist? You will need to think about many aspects before making a commitment to either option. Read on to see our take on whether you should go for an in-house or an outsourced ML team.
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