Last updated on November 9th, 2022 at 12:13 pm

My Journey to Mastery in Natural Language Processing

As we already know, the field of data science is quite broad. Building a successful career in data science is a huge task in itself, which needs proper mentoring and guidance from experts.  Here, you can find numerous branches of study, each branch is concerned with a specific concept. One such branch of learning in data science is natural language processing. Ample study materials and tutorials are available to learn NLP in data science, but the learning process is not known to all. Thus, it becomes a great help if someone shares their journey or helps in navigating yours.

To start off with your journey of mastering natural language processing needs a dedicated mind and a helpful roadmap. The first requirement must be fulfilled by you and I can help you figure out the roadmap of your journey by sharing mine. Firstly, anyone who is planning a career in data science or wants to master NLP, must understand its meaning deeply. So, we also must start with understanding the meaning of NLP, and then proceed further. 

What is NLP?

The National Language Processing is an area of research study in artificial intelligence which concentrates on understanding human language as it is spoken or written. If one digs deep, they will know its history in the field of linguistics and data science, which existed for a long time now. This ability of a computer program is applied in various real-world industries. For example, it is used in medical research, search engines, as well as in business intelligence. 

One major application of NLP is in the field of data science, as it is impossible to analyse and process huge data without natural language processing. 

After you understand the basics of NLP, it is time to go in depth of the skills you must gather to go smoothly in your journey of mastering natural language processing. 

Here are some skills that  you should gain and move forward in your learning process; 

• Programming

It is well known in the technical field that programming is one of the essential skills to acquire. Once you learn programming, it becomes easy to apply it in mathematics and statistics as you go on. Based on your application, you can go on gathering knowledge in programming. As we are discussing about NLP, the minimum requirement is to have basic knowledge of programming in any programming language. To give you some relief, I must let you know that learning a programming language is not hard if you go in with a dedicated mind. 

• Mathematics

After you have a basic knowledge of programming, then you can apply it in mathematics, statistics and probability, quite easily. But before that, you must know the various aspects of maths. As mathematics is a vast field and a huge part of both data science and NLP, it is of utmost importance to study the prime aspects of it thoroughly. The main fields of study here are linear algebra, calculus, probability, and statistics. 

• Machine learning 

One of the important concepts to study in data science is machine learning which is also a broad area of study. But to understand natural language processing algorithms deeply, one must be familiar with machine learning algorithms. Some of which are supervised, unsupervised, and transferred learning. You can get a good knowledge of this combined with NLP and of entire data science from a post-graduate program in data science and machine learning. This data science course with job placement will not only make you an expert but help you gather professional experience as well. 

• Text Preprocessing 

Now, it's time to learn the NLP basics, and the first step to it is to understand the text preprocessing. Under this, there are several procedures that are undertaken to go further in the analysis process of a text. Briefly, it comprises concepts like stemming, tokenization, stopword removal, lemmatization, and many more. All you need to do is to understand the concepts and their uses to apply it appropriately. 

• Core NLP techniques

Lastly, after learning about different concepts and acquiring various skills, it is important to understand the core techniques of natural language processing. As text preprocessing makes the text ready for further analysis, the core techniques of NLP analyses it thoroughly. It aims to perform a set of specific tasks to extract useful information from the text. 

These techniques are building sequence models, parsing text to extract syntactic representation, classifying texts, applying language models, and many more. 

Along with learning these techniques, it is mandatory for you to keep track of recent development of the field, both technological and academic.

Conclusion

Once you master natural language processing, you also cover a huge part of data science study. This will help you build a career in data science, a field that has a bright future ahead. So, it is advisable to all the newcomers to get started with your journey of mastering NLP. There are endless possibilities waiting for you on the other side.