Under the umbrella of data science fields, natural language processing (NLP) is one of the most famous and important subfields. Natural language processing is a computer science field that gives computers the ability to understand human — natural — languages.
Although the field has gained a lot of traction recently, it is — in fact — a field as old as computers themselves. However, the advancement of technology and computing power has led to incredible advancements in NLP.
Now, speech technologies are becoming as famous as written text technologies. …
Natural language processing (NLP) is with no doubt — in my opinion — the most famous field of data science. Over the past decade, it has gained a lot of traction “buzz” in both industry and academia.
But, the truth is, NLP is not a new field at all. The human desire for computers to comprehend and understand our language has been there since the creation of computers. Yes, those old computers that could barely run multiple programs at the same time, nevertheless comprehend the complexity of natural languages!
Natural language processing — if you’re new to the field — is basically any human language, such as English, Arabic, Spanish, etc. The difficulty behind giving computers the ability to understand natural languages is how complex they can get. …
One of the most well-known and essential sub-fields of data science is machine learning. The term machine learning was first used in 1959 by IBM researcher Arthur Samuel. From there, the field of machine learning gained much interest from others, especially for its use in classifications.
When you start your journey into learning and mastering the different aspects of data science, perhaps the first sub-field you come across is machine learning. Machine learning is the name used to describe a collection of computer algorithms that can learn and improve by gathering information while they are running.
Any machine learning algorithm is built upon some data. Initially, the algorithm uses some “training data” to build an intuition of solving a specific problem. Once the algorithm passes the learning phase, it can then use the knowledge it gained to solve similar problems based on different datasets. …
Job hunting is always a hassle. It’s a brutal game, where you need to stand out among hundreds and sometimes thousands of other applicants to get “the job.” But, finding a job to apply for in the first place is not an easy task.
When I first started with data science, I was baffled about the different data science-related roles' responsibilities. I didn’t want to choose a role that I am not completely sure about what I will be doing.
Because of the many roles and the different names, applicants may get confused and not know which role matches their specific skillsets or what they want to work on. …
Landing a good job in data science can be quite a challenging and difficult task. Although data science is rapidly growing, the number of people getting interested in the field or joining in for financial reasons is increasing exponentially.
So, despite the fact that the demand for good data scientists is high, finding a job as a data scientist is extremely difficult. In order to get a job, you will need to stand out among hundreds, if not thousands, of other applicants.
There are many aspects to a good data scientist, some are technical aspects, while others are not. As a data scientist, you need to have a strong that portfolio clearly demonstrates their technical skillset, as well as their soft skills. …
The high demand for programmers, developers, and data scientists attracted many people to join the field of IT. But, most often, newcomers try to take the fast track through the learning process to land a job faster.
Rushing the learning process is not always a good thing; in fact, sometimes, people may tend to skip over some important aspects of the field in their attempt to shorten their learning period or because they find them intimidating.
“The biggest mistake I see new programmers make is focusing on learning syntax instead of learning how to solve problems.” — V. Anton Spraul
Regardless of your target career — software developer, web developer, or data scientist — all IT-based career share one thing in common, that is, programming knowledge. …
Along the way on your programming journey, there are a few milestones that you need to conquer to advance ahead. For example, getting comfortable with classes, understanding pointers, master the art of functionalizing your code, and so on. One of the trickest programming concepts to learn for newcomers and master for those who have been programming for a while is recursion.
When I first started to code — almost a decade ago — I struggled a bit in wrapping my head around recursion. While some people can naturally think recursively, others — myself included — can’t.
Thinking recursively is something you can train your brain to do and master, even if you’re not born with this ability. …
Suppose you’re a software developer, a data scientist, or a programmer. In that case, you must have come across Git at some point along your journey. Mastering version control is one of the essential skills that is shared among all software-related fields.
Version control systems are a particular type of software designed to help programmers track any specific application source code changes.
In general, there are two types of version control systems, centralized and distributed systems. The main difference between those two types is, in centralized systems, the code files and the information about the contributors are stored in a single server. …
Open-source is probably one of the buzzwords of today’s tech world. As a developer or a data scientist, you’ve probably heard of it before. Even if you were not in a deeply technical field, the chance is you’ve heard someone mention the topic of open-source.
Although many are familiar with the term open-source, it’s not always true that people really know what that term means.
So, what’s open source?
Open-source is a type of software in which the source code of this software is released under a specific copyrights license for others to use, study, change and distribute the software for any purpose — as long as it doesn’t contradict the copyright license. …
When I first started reading on Medium back in 2017, I didn’t pay attention to articles that were trending or, as Medium used to describe it, “popular on Medium.”
when I started following Zulie Rane on YouTube, it was the first time I heard about all the different parameters that get you noticed on Medium.
Back then, I always thought only popular authors get trending and must get tons of views and possibly a good amount of money for that!
I only started writing on Medium in July 2020. I always loved writing but was afraid of putting myself out there. Watching videos from top writers and reading articles about how writing on Medium felt quite fulfilling to me, so I took a leap of faith and started writing my heart out. …