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Get Your AI to Production Faster: Accelerators For ML Projects

One of the worst-kept secrets among data scientists and AI engineers is that no one starts a new project from scratch. In the age of information there are thousands of examples available when starting a new project. As a result, data scientists will often begin a project by developing an understanding of the data and the problem space and will then go out and find an example that is closest to what they are trying to accomplish.

The Benefits of Exploratory Testing in Agile Environments

Agile software development places significant value on faster processes and better-quality outcomes, but there are a lot of different techniques that teams can leverage to achieve these goals. For many, automation integration has become a major priority, but there are several benefits to be seen from manual operations like exploratory testing. Let's take a look at what advantages exploratory testing can bring to agile environments.

Cypress vs Selenium: Features, Pricing and More Compared

Cypress and Selenium are two of the most popular website testing tools. Each has advantages, so it can be tough to know which is the best fit for you. That’s why we’ve compared and contrasted the two, so you know which is best for specific use cases. As makers of our own web testing tool, we’re very familiar with what makes one work well. In this article, we’ll give you a complete, unbiased breakdown of Cypress vs Selenium.

A Software Engineer's Tips and Tricks #3: CPU Utilization Is Not Always What It Seems

Hey there! We're back for our third edition of Tips and Tricks. As we said in our first posts on Drizzle ORM and Template Databases in PostgreSQL, our new Tips and Tricks mini blog series is going to share some helpful insights and cool tech that we've stumbled upon while working on technical stuff. Today's topic is short and sweet. It'll be on CPU utilization and what that metric indicates. If you enjoy it and want to learn more, I encourage you to check out the "further reading" links.

Artificial Intelligence vs. Intelligent Automation: What's the Difference?

AI injects “intelligence” into automation, enabling systems to execute tasks, comprehend complex data, make informed decisions, and learn from outcomes. Unlike technologies such as robotic process automation (RPA), which follow predetermined rules, AI leverages data to evaluate situations and determine the best course of action. Now that we've explored how AI augments traditional automation tools, let's delve deeper into the realm of intelligent automation.

What The Future of #Blockchain Testing Looks Like? | Gomathi Ramalingam | #QonfX 2024

In this session, Gomathi Ramalingam explores the future of blockchain testing in her enlightening talk, "Beyond the Block: Pioneering the Future of Blockchain Testing." Discover the necessity for testing approaches to evolve alongside blockchain technology as it gains broader acceptance across industries.

How to Set Up Pre-paid Credit-Based Billing With Stripe

In today’s subscription-driven economy, flexible billing options are crucial. While traditional post-paid models are widespread, pre-paid credit-based billing is gaining popularity. This approach empowers businesses to bill customers upfront for a set amount of usage, offering an alternative way for customers to pay for your service.

Adding Colour To The Log Output Of Logging Libraries In Go

Logging is an integral part of software development, providing developers with valuable insights into the behaviour and performance of their applications. In the Go programming language, various logging libraries, such as the standard library’s log package or third-party options like logrus , zap and zerolog, facilitate the generation of log output.

White Box, Gray Box, and Black Box Testing - Unpacking The Trio

Functional testing is important in the software development process and is employed by around 90% of development teams, according to Huttle Research. It ensures software performs as intended through different methodologies such as white box, black box, and gray box testing. However, choosing the right approach can be complex, involving considerations like project requirements, team expertise, and specific software characteristics.