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Serving machine learning models as an API is a common approach for integrating ML capabilities into modern software applications. This process helps to simplify the development of applications and has multiple benefits, such as scalability, efficiency, flexibility, and accessibility. Basically, the aim of such an API is to integrate machine learning models into other components of the application, which enables the use of the predictive power of machine learning in real time. So, this process al

Using microservices for building apps is rapidly gaining popularity as they can bring so many different benefits to the business: they are safe and reliable, scalable, optimize the development time and cost, and are simple to deploy. In our previous articles, we discussed the best tools to manage microservices, the advantages and disadvantages of using microservices and the differences they have with monolith architecture, and hexagonal architecture. Despite multiple benefits, app development

Well, 2020 has proved that making predictions is at least naive today. But when it comes to the mid or long-term investment decisions, things are getting more serious. It is also crucial for developers to plan their careers and invest time efficiently. So please welcome the most significant trends of Java that will help you stay tuned up. Java remains among the most popular languages for web, desktop, and mobile development and embedded software. It was the only official language for Android dev

Before we delve into the details of Docker and Docker Compose, let us define the principal idea of containerization. Skip to the following blocks without any ado if you are eager to reveal Docker’s nuts and bolts immediately. To the rest of the readers:” Welcome on board, cabin boys and girls!” Container technology today is mainly associated with Docker, which also helped to accelerate the overall trend of native cloud development. Meanwhile, technology is rooted in the 1970s, as Rani Osnat tell

Facebook developed GraphQL as a major problem-solver for more efficient mobile data loading in 2012 and released it as an open-source solution three years later. Since that time, it mistakenly associates with PHP only and lacks trust given Facebook’s reputation (if you know what I mean). However, a recent Netflix case that finds GraphQL as a game-changer to power the API layer and increase the scalability and operability of the studio ecosystem attracts attention. This specification already gain

Docker, an enterprise container platform is developers’ favorite due to its flexibility and ease of use. It makes it generally easy to create, deploy, and run applications inside of containers. With containers, you can gather applications and their core necessities and dependencies into a single package turn it into a Docker image, and replicate it. Docker images are built from Dockerfiles, where you define what the image should look like, as well as the operating system and commands. However, l

When our team’s project scored first in the text subtask of this year’s CALL Shared Task challenge, one of the key components of our success was careful preparation and cleaning of data. Data cleaning and preparation is the most critical first step in any AI project. As evidence shows, most data scientists spend most of their time — up to 70% — on cleaning data. In this blog post, we’ll guide you through these initial steps of data cleaning and preprocessing in Python, starting from importing th

In contrast to our usual theoretical posts, in this story, we will discuss our recent adaptation of the popular Lyon’s auditory model for Python. The ability of the human auditory system to recognize speech in adverse and noisy conditions has prompted researchers to introduce features of human perception in speech recognition systems. The early 1980s saw an outburst of computational models based on physiological measurements of the response of individual auditory nerve fibers. One of the models