Top Differences Between ML, Deep Learning, And NLP

The ongoing debate between Machine Learning, Deep Learning, and Natural Language Processing has been around for quite a while now.

For many, these three terms are confusing due to their correlation with one another. Consider this: Artificial Intelligence governs machine learning and natural language processing. Deep Learning, on the other hand, is the child of machine learning. 

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Before we get directly into the standing differences between ML, Deep Learning, and NLP, let’s have a look at what they mean. 

What is Machine Learning?

If we had ways to establish a strong AI architecture, machine learning would have had its domain. 

What is the difference between normal learning vs machine learning? 

Machine Learning is one way of training machines. Earlier, traditional approaches were used for training machines. Understand this with a simple example, you want to build software that is explicit to be used for Bitcoin trading. You are aware of the algorithm that will yield you the results that you are looking for. Therefore, all you do is feed the necessary inputs to create the algorithm that will serve you the required output. This is called normal learning. 

Now let’s head towards a reality where the scene is a little different. Several factors can influence Bitcoin movements. These include CSI, MACD, RSI, etc. Eventually, it will become difficult to comprehend the exact operation that is being used. So, all you do is make a system that takes all these values and combines them. It tries to create a mathematical formula. It needs more bitcoin data, and you keep feeding it so that it retrieves accurate results. This is machine learning. The machine is learning from its own experience.

What is Deep Learning?

An extended branch of ML is Deep Learning which uses Artificial Neural Networks (ANNs) to the maximum to mimic the way the human mind works.

Speaking of ANNs, they contain tons of neurons that are piled to form multiple layers. This is where the name “Deep Learning” comes from. The neural network needs humongous data to function and run through neurons. Every neuron facilitates an activation function which gets activated when a certain threshold is reached. Deep Learning primarily focuses on working with neuron networks in large numbers. Deep Learning is primarily used for NLP, Object Recognition, etc.

What is Natural Language Processing?

Natural Language Processing is a subset of Artificial Intelligence that combines ML algorithms to process different languages like Hindi, English, Spanish, etc. 

As we know, the same words can have different meanings, pronunciations, grammatical syntaxes, etc. All of this is achieved through NLP. Moreover, NLP can also be used for translation, i.e., converting from one language to another.

Difference between Machine Learning and Deep Learning

The key differences between machine learning and deep learning are: 

• Deep learning is a child/subset of machine learning. They both are governed by Artificial Intelligence. Deep learning is capable of empowering AI.
   
• Machine Learning works around algorithms for parsing data. Moreover, it uses the same data to derive useful information from it and make decisions based on information.
   
• Deep learning generates an artificial neural network that can become intelligent on its own as well as make eligible decisions.
   

The differences between machine learning and deep learning offer valuable insight into how data is being molded.

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Difference between Machine Learning and Natural Language Processing

Let’s roll on to see the basic difference between machine learning and NLP.

• NLP is a subset of machine learning wherein the computer learns how to comprehend what two human beings are conversing about. Machine learning lets computers work with previous data by running it without any supervision or programming, applied to any domain.
   
• NLP aims to build a smart computer that is capable of communicating like humans. ML allows machines to understand data and automatically execute it to yield accurate results.

Difference between Machine Learning, Deep Learning, and NLP

Now that the difference between machine learning and NLP and the difference between machine learning and deep learning is sorted, let’s get to know the differences between ML, DL, and NLP.

• Applications – ML, DL, and NLP have their branches of applications.
   
• Machine Learning is extensively used on social media platforms. The algorithm and techniques are used to build some user-friendly features. Machine learning learns from your experiences, and makes suggestions accordingly.
   
• Deep Learning assists in detecting fraud. Due to digital growth, there has been a massive growth in fraud. With the deep learning technique, such anomalies can be detected.
   
• Natural Processing Language can be seen in chatbots which are mainly created to interact with humans directly. They are designed in such a way that they maintain similarity in conversation like humans.
   
• Salary: The salary of each of these fields vary, however, the packages are certainly attractive.
   
• The average annual package for Machine Learning engineers is INR 7.5 LPA.
   
• Deep Learning engineers make an INR 7 – 12 LPA carrying an experience of 8 years.
   
• The average salary of an NLP Engineer is INR 8.5 LPA.
   
• Function: DL, ML, and NLP, all have their own set of functions.
   
• Deep Learning aligns with supervised learning to supervise large neural networks that use unstructured data.
   
• Natural Processing Language is concerned more with the way computers can process, analyze, and decode human languages. To do so, several methodologies and technologies are used.
   
• Machine Learning uses systems and approaches that systems can extract from data. Furthermore, this data learning can be used to identify patterns or make decisions without any human supervision.

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Conclusion

Deep Learning, Machine Learning, and Natural Processing Learning belong to a broader section of the study. Every technology is busy reinventing the processes or making a new one by redefining the way humans behave. 

The future is going to introduce us to more possibilities, applications, and functions of AI, ML, DL, and NLP. Through the refined differences between AI, ML, and DL, the concepts can be magnified. 

If you are interested in knowing more about any of these domains, you can explore the courses Master of Science in Machine Learning & AI or the Executive Post Graduate Programme in Machine Learning & AI in association with upGrad. Also, the Advanced Certificate Programme in Machine Learning & NLP and the Advanced Certificate Programme in Machine Learning & Deep Learning are some of the great considerations if you wish to dive into this field.

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