NLP90 : Self-learn NLP in 90 hours

NLP90 : Self-learn NLP in 90 hours


Pre-requisites :?Basics of Machine Learning

The content is designed so that you spend 6hrs per week for around 15 weeks making it 90 hrs (assuming good familiarity with general ML algorithms and Python).

Natural Language processing How and why?

What is NLP?

Natural language processing (NLP) is the use of human languages, such as

English or French, by a computer. Computer programs typically read and emit

specialized languages designed to allow efficient and unambiguous parsing by simple programs. More naturally occurring languages are often ambiguous and defy formal description. Natural language processing includes applications such as machine translation, in which the learner must read a sentence in one human language and emit an equivalent sentence in another human language. Many NLP applications are based on language models that define a probability distribution over sequences of words, characters or bytes in a natural language.

As with the other applications discussed in this chapter, very generic neural

network techniques can be successfully applied to natural language processing.

However, to achieve excellent performance and to scale well to large applications, some domain-specific strategies become important. To build an efficient model of natural language, we must usually use techniques that are specialized for processing sequential data. In many cases, we choose to regard natural language as a sequence of words, rather than a sequence of individual characters or bytes. Because the total number of possible words is so large, word-based language models must operate on an extremely high-dimensional and sparse discrete space. Several strategies have been develop ed to make models of such a space efficient, both in a computational and in a statistical sense.

How it works?

NLP might appear like magic or hypnosis. During therapy the subject goes deep into their unconscious mind and sifts through layers and layers of beliefs and perceptions to become aware of an experience in early childhood that is responsible for a behaviour pattern. NLP works on the principle that everyone has all the resources they need to make positive changes in their own life. NLP techniques are used as a tool to facilitate these changes.


NLP Therapy can be content free. That means the therapist can be effective without knowing about the problem in great detail. Hence the therapist need not be told about the event or even the issue, thereby ensuring privacy for the client. Besides this we also have a non- disclosure agreement in which the interaction between the client and the therapist is kept confidential.

NLP believes in perfection of nature in human creation. Hence NLP encourages the client to recognize their sensory sensitivities and use them to respond to a particular problem. In fact, NLP also believes that the mind is capable of finding even cures to ailments and diseases.

NLP techniques involve noninvasive, medicine free therapy that helps the client discover new ways of dealing with emotional problems such as low self-esteem, anxiety, lack of confidence, destructive relationship patterns (coping with breakup), and are successful ineffective bereavement counseling.

NLP has its roots in the field of behavioural science, developed by Pavlov, Skinner and Thorndike. It uses physiology and the unconscious mind to change thought processes and therefore behaviour.

Advantages of NLP

With natural language processing, computers can infer and analyze human language with more meaning than simply digesting and outputting programmed responses. In this sense, NLP offers greater use and interaction with humans.


NLP enables more natural conversations, more efficient operations, reduced costs, higher customer satisfaction, and improved analysis. Creating an NLP chatbot or adding NLP capabilities to your existing chatbot is easier than ever before, with the advantages vastly outweighing the associated costs.

Disadvantages of NLP

NLP provides a limited number of techniques, that are not suitable for many clinical situations or that make significant change. They can change the way someone feels in the moment, but doesn’t change the underlying issues which have created the situation. Used in conjunction with other techniques, they can have value. As change techniques, people should be advised to have proper training beyond 7 days of NLP (dealing with abreactions, clinical assessment, etc) and have appropriate insurance before using them with clients.

Week 1 : Reading

https://towardsdatascience.com/your-guide-to-natural-language-processing-nlp-48ea2511f6e1

https://medium.com/@ageitgey/natural-language-processing-is-fun-9a0bff37854e

https://www.nltk.org/book/ch01.html

Week 2 : Word Tokenization and Sentence Segmentation

https://stanfordnlp.github.io/stanza/tokenize.html#start-with-pretokenized-texthttps://www.nltk.org/api/nltk.tokenize.html

https://www.guru99.com/tokenize-words-sentences-nltk.html

Week 3 : Stemming and Lemmatization

https://www.guru99.com/stemming-lemmatization-python-nltk.html

https://www.nltk.org/book/ch03.html

Week 4 : N-gram models

https://medium.com/swlh/language-modelling-with-nltk-20eac7e70853

Week 5 : Naive Bayes & Sentiment Classification

https://www.analyticsvidhya.com/blog/2021/07/performing-sentiment-analysis-with-naive-bayes-classifier/

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