Do Machine Learning Engineers Need To Know Data Structures And Algorithms?

Do Machine Learning Engineers Need To Know Data Structures And Algorithms?

As a programmer, you probably spent the early days of your career analyzing code syntax and package libraries, and learning the latest in your chosen discipline. But what do you need to know about data structures and algorithms? And is this knowledge necessary to advance in your career? Computer programming has come a long way from the early days of programming languages ​​to today’s modern programming languages. Despite increased complexity, power, and efficiency, the basic concepts and uses of data structures and algorithms in computer programming haven’t really changed.

Read More : Need of Data Structures and Algorithms for Deep Learning and Machine Learning

WHAT IS DATA STRUCTURES AND ALGORITHMS (DSA)?

You may not know the classic or functional definition of a data structure and an algorithm, but you certainly use them in your day-to-day life. Data structures and algorithms are a branch of computer science that deals with creating optimized and efficient computer programs for machines. The term data structure refers to the storage and organization of data, and algorithm refers to the step-by-step process to generate a desired result.

In other words, data structures are a means of cataloging and indexing data, while algorithms are mini-programs, independent of the code in which they reside.

Take the example of the metric and imperial systems. Suppose we have code that converts imperial measurement units to metric units. Values ​​are received in miles or kilometers and sorted into the correct bin. These are your data structures. The algorithm refers to the conversion rate or (miles (m) = kilometers (km) x 1.609344)

Essentially, DSA is the cornerstone of the software development process. It applies to all programming languages ​​and technologies, and the terminology remains largely the same between disciplines.

REASONS TO LEARN DATA STRUCTURES AND ALGORITHMS

For many people, data structures and algorithms are just a useless module in their computer science degree. DSA is much more than that: it teaches you to become a better programmer and to think better. It’s a skill that will help you in surprising ways throughout your career.

1.DSA is a basic coding concept

Data structures and algorithms are the foundations of software development. They stay the same no matter what new technology is used, and this puts the focus on the problem, not the technology, in the servicing process.

2. OPTIMIZATION

Code is often a delicate balance between intensive system resources and data sources. Engineers with a good understanding of data structures and algorithms are good at managing, classifying, and storing information. They know the efficient techniques required to perform any data operation. You know which model to follow when building data-driven applications. This optimizes both the code and the system to increase processing power and efficiency.

3. LEARN NEW TECHNOLOGIES QUICKLY

As a software developer, knowing how to access, organize and interpret data is invaluable. If you understand algorithms and how they can efficiently process this information, you will be better prepared to adopt new frameworks and master more of them.

4.DSA ENCOURAGES CREATIVITY AND INNOVATION

Engineers who understand data structures and algorithms tend to approach coding problems differently. A pure programmer will look at the problem from a syntax and coding perspective, while an engineer familiar with DSA will see the big picture. With an understanding of data structures and algorithms, programmers can visualize how different elements interact long before writing a single line of code. DSA skills are a good basis for measuring a candidate’s ability to problem solve, think analytically, and organize information. It is this creative perspective that often prompts programmers to take on greater architectural design tasks and exert greater influence over technical direction.

5. START-UPS AND FAANGS PREFER CANDIDATES WITH EXCELLENT DSA SKILLS

Tech startups and FAANGs are increasingly looking for engineers with a solid understanding of data structures and algorithms. It might hurt to listen, but programmers are a gem these days. Most people can understand a programming language, but only truly amazing engineers will understand how to solve problems creatively using an analytical approach. Additionally, most tech startups want engineers who can get started, especially if your engineering organization is in its infancy. Resources are likely to be scarce, so you need people who can contribute from day one.

DO YOU NEED TO KNOW ABOUT DATA STRUCTURES AND ALGORITHMS TO GET A CODING JOB?

The short answer is no. Many companies simply hire people based on a very specific technical skill and/or level of experience. That’s perfectly fine if that’s what you want, but it’s like learning to play the piano but only the treble clef notes in your right hand. Sure, you can get away with it, but it could be a whole lot better.

Being a pure programmer (no DSA knowledge) can work for years, that is, until you find a scaled product.

Let’s say you’re working on an internal SSO messaging platform for a small business, and the company decides to dramatically increase its user base while incorporating MFA into its enrollment process. Without knowledge of data structure and algorithms, you are blind when trying to allocate resources to scale parts of the code. With the knowledge of DSA, you can determine in advance what is feasible and what resources will be required.

Startups and FAANGs typically hire engineers with strong DSA skills because they are more likely to innovate and develop unique and scalable solutions to new and existing problems.

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