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In the previous post, we explored the structure of a Spring Boot application using advanced modular architecture. This time, let’s shift gears to discuss how to enhance observability in Spring Boot microservices and applications. Specifically, we’ll delve into how integrating Micrometer, OpenTelemetry, and the Spring Modulith Starter Insight can offer... [Read More]

Advanced practices in software development not only streamline production but also enhance the maintainability and scalability of applications. This blog post delves into constructing a Spring Boot application, utilizing Docker for consistent local environment, Zipkin for tracing, and strategies to achieve 100% code coverage. We’ll explore setting up a feature-based... [Read More]

Testing is a crucial part of any application development process, especially when building RESTful APIs with Spring Boot. In this blog post, we’ll walk you through a practical example of testing CRUD (Create, Read, Update, Delete) REST APIs for a Person entity using Spring Data JPA with H2 as the... [Read More]

In this blog post, we will embark on an exciting journey of building a full-fledged Spring Boot Monolith application implementing CRUD (Create, Read, Update, Delete) operations on a Person entity. We’ll leverage JPA for data persistence, Swagger for API documentation, Postgres as our database, and Vue.js 3 for the front-end.... [Read More]

The Fashion-MNIST is a dataset of Zalando’s article images. It serves as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. This dataset includes 60,000 training examples and 10,000 test examples, each being a 28x28 grayscale image associated with a label from 10 classes. [Read More]

Understanding neural networks is one thing, but seeing them in action is quite another. The MNIST database, a large collection of handwritten digits, is the perfect playground to train and test a neural network for image recognition. In this blog post, we will build upon our previous “Crafting a Neural... [Read More]

In the realm of machine learning and pattern recognition, the MNIST dataset stands as a benchmark for algorithms and methods. It’s akin to the hello world of machine learning for classification tasks. Before delving into the technicalities of multi-class classification, let’s embark on a journey to fully understand the MNIST... [Read More]

In today’s era of expansive libraries and frameworks, the idea of crafting a neural network from scratch might seem daunting. Even more so, doing it in a single file? Almost unheard of! Yet, with the power of jbang and the versatility of Java, this task becomes not only feasible but... [Read More]