Alrighty then! Let’s pick up from where we left off in Part 1. Buckle up, and let’s dive right in! Implementing gRPC Services Server-side Implementation A. Define Service Methods Let’s use the hello world example from the part I section: syntax = "proto3"; option java_multiple_files = true; option java_package = "com.example.grpc.helloworld"; option java_outer_classname = "HelloWorldProto";…
Understanding gRPC gRPC and its purpose gRPC is a modern Remote Procedure Call (RPC) framework. But what does that mean? Think of it like this: imagine you have two computers, and you want them to communicate with each other. You could do that by sending messages back and forth, but that can be tedious and…
When developing a new product or adding fresh features to an existing one, it’s crucial to understand what our customers want and need. Whether the product is for an internal team or external users, the question remains the same – what features should we develop to satisfy our customers? Many organizations use popular frameworks to…
Understanding the Basics Well, let’s get the ball rolling with a dinner party analogy. Imagine throwing a dinner party for a hundred guests – all fun and games, right? But keeping tabs on all of them is a nightmarish task. Now, imagine if you could group these guests into ten tables, based on similarities, like…
Organizations are harnessing the power of artificial intelligence (AI) and machine learning (ML) to gain insights into customer behavior, operational efficiencies, and numerous other business challenges. As a result, companies are making substantial investments in data science technology and teams to develop and train analytical models. While these investments pay off, the real jackpot lies…
Let’s chat about one of the most fundamental techniques in machine learning and statistics – Linear Regression, which forms the backbone of many advanced techniques, so it’s a great place to start. Understanding the Basics Linear Regression is like the Swiss Army knife of statistics. It’s a predictive modeling technique that finds the best-fitting straight…
Let’s talk about regularization in machine learning, a really handy concept that helps us build better predictive models. In machine learning, we’re often trying to make predictions based on data. For example, we might want to predict the price of a house based on its size, location, and other factors. To do this, we build…
Scala collections systematically distinguish between mutable (scala.collection.mutable) and immutable (scala.collection.immutable) collections. A mutable collection can be updated or extended in place. This means you can change, add, or remove elements of a collection as a side effect. Immutable collections, by contrast, never change. You have still operations that simulate additions, removals, or updates, but those…
Generic types allows us to abstract over types. If we don’t care what type is stored but we want to make sure we preserve the type when we get the value out, then use a generic type. Generic classes or traits takes a type parameter within a square bracket [ ]. The Scala convention is…
Traits allow us to express that multiple classes share a common super-type. Traits are similar to Java’s interfaces and can be thought of abstraction over classes. // Trait declaration trait TraitName { declarationExpression } // declare class is a subtype of trait class Name(…) extends TraitName { … } Two ways that traits are different…