AWS Elastic Beanstalk for NodeJS makes it easy to deploy, manage, and scale your Node.js applications using Amazon Web Services.

Manual deployment of a Typescript Node.js server to Elastic beanstalk is a tedious process. The hard way is to first compile your code, compress the compiled code and upload it to Elastic Beanstalk or use AWS Code deploy pipelines. The problem with pipelines is that you will have errors compiling typescript on EB. Unless you build locally and deploy your code with the build — not ideal.

The ideal scenario is to use a CI/CD service to run those tasks…

State management

Every React component (both class and functional) can have a state. A state is basically a JavaScript object that represents the part of a component that can change. Typically, a change in a component state affects other components. Using local state is fine when working with simple or lightweight apps. But not efficient with huge applications. Having a global state management is ideal when working on complex applications. Combining React’s context API with state, you can easily implement global state management without using 3rd party libraries like Redux. Here is a simple example

Machine learning projects are about taking data inputs, training models, testing and predicting new instances data. To do this, there are crucial steps that needs to be accomplished.

Steps for a typical predictive model workflow

1. Gathering Data

The process of gathering data depends on the type of project we are working on. Data can come from different sources, with different data formats. For example, if we are working on a computer vision-based project, then our data will likely be images. For most other machine learning projects, the data will be presented in a tabular form, similar to spreadsheets. The data set can…

Machine learning and AI are often used interchangeably but they are not exactly the same thing. Machine learning is more like a subset of Artificial intelligence. In my previous article on artificial intelligence, i mentioned that machine learning is the backbone of AI just as our learning capacity serves as the backbone of human intelligence, among other cognitive abilities. Check out that article here

Machine learning refers to algorithms that computers use to learn from data, allowing it to make predictions on future, unseen data. Development began somewhere in the 50s, but it didn’t really thrive until the late 2000s…

Let me warn you that this article is quite long but contains some valuable information, so ill ask that you hang in there with me : )

Design is a useful skill for any profession. We all use design all the time — creating a presentation; arranging the furniture in your living room; formatting your resume; coming up with an architecture for a software,etc. Design is basically how you present information so other people can understand and intuitively use it.

Product design is how both the interface and functionalities work to solve the user’s problem and the experience they get…

The term AI has gained a great deal of hype. Everyone seems to be talking about it these days, on many different levels. It’s really exciting but also confusing. If you are like me, you probably tried to make sense of it to keep up with the trend, but you just couldn’t get a good understanding of the topic due to the sheer number of jargon. In this post, I will try to break it down.

AI is a broad topic under computer science! It ranges from something as simple as the calculator on your phone to more complex things…

Albert Akrong

Software engineer and AI enthusiast.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store