The R programming language is one of the most popular programming languages right now. As such, the comparison is quite often made between R and other popular programming languages, such as R vs. Python and R vs. Matlab.
R has an exhaustive number of packages. It is open source and completely free to use. Active community support for the statistical programming language is also available. These are just some of the several reasons to get started with R today.
MySQL 8 is one of the most popular database engines. It can assist link thousands of databases to servers once configured correctly and at comparatively low prices. Additionally, as it’s such a common tool, you’re unlikely to run into issues where servers don’t acknowledge it or configure it to do what you want it to do.
There may be few situations when using MySQL 8 where you will not be able to access or use MySQL correctly. These can be very unpleasant situations, but they can be readily fixed. However, you must understand the issue before you search for the solution!
A popular development environment, Ruby on Rails features a simple syntax. The environment is accommodating by nature, allowing teams of varying sizes to work in complete harmony. Developers find it fairly easy to learn, and thus, it is one of the most popular development technology available today.
Thanks to Apple, the web development framework saw an overnight upsurge in its popularity. However, in 2012, security breaches invited massive criticism from its patrons.
Have you encountered an error that says, “PHPMailer SMTP Error: Could not connect to SMTP host?”
Let’s solve it together.
The document signing process plays a crucial role, as it guarantees the creation of binding obligations between the signing parties.
The sales contract looks legalized, have all the parties signed it? Is it the reviewed and latest version? Can it be proved that the document has not been altered before you signed? Is it possible to prove the document you received is identical to the one you viewed earlier?
Think about how much faster you could sell or help customers by having a chatbot or virtual assistant handling orders. An order process has certain information that needs to be filled out in order to complete the process. When you are building a bot, this is called slot filling. This guide is a walkthrough on how you create a slot filling flow.
You might also like: Slot-Filling Chatbots Will Never Meet Human Expectations
Slot filling is about collecting certain bits of information from the user before a final response can be given. A typical use-case is to make an order of some kind where certain parameters need to be settled before the order can be placed, for example booking a flight or ordering a pair of shoes.
Elasticsearch is a popular solution option for searching text data. Recently, we used it to build employee search functionality in one of the web applications on GCP.
In short, we wanted to be able to search employees by the initial few characters of the "name" of the employee. Plus:
The case behind this article aimed to complete a large-scale project in a short amount of time. Obviously, you just need to hire a lot of people, and then you have to make sure they don’t hinder each other. The latter is the most complicated; there is no way to make it happen without a good technical approach — and that’s what exactly we are going to talk about.
Our team has been working on a large mobile app for a major telecom company. The app has its "core" functionality (main use cases), and some extensions that offer additional use cases — but, essentially, the app can work without them. Further, we will refer to these extensions as "features."
Recommender systems promise to reduce churn and increase sales. But how do you measure their actual success? What is it that you should measure? And what challenges should you look out for when you’re building your recommendation engine? In this article, I’ll discuss some challenges of recommendation engines, the ROI, and standard metrics to help evaluate their performance.
You might also like: Building a Recommendation System Using Deep Learning Models
Most articles about recommendation engines focus on all the bright sides of recommendations: personalized customer experience, lower churn, increase in sales, and more revenue. While all of that is true, as we can see looking at the examples of numerous companies including Amazon, adopting a new technology requires a strategic approach — so you should be realistic and well-prepared and not only optimistic about the future outcomes. There are some challenges that you have to be aware of.
In one of my previous posts, we discussed Domain and Integration events. In this post, we will look at modeling domain events in order to simplify the application.
You may also enjoy: The Role of the Domain Model With CQRS/Event Sourcing
There are certain triggers that can lead to domain events.
