docs(README): update as per the revised documentation

README.md

@@ -13,29 +13,29 @@ winkNLP is a JavaScript library for Natural Language Processing (NLP). Designed
 ## Features
 It packs a rich feature set into a small foot print codebase of [under 1500 lines](https://coveralls.io/github/winkjs/wink-nlp?branch=master):
 
-1. Lossless & multilingual tokenizer
+1. Fast, lossless & multilingual [tokenizer](https://winkjs.org/wink-nlp/processing-pipeline.html)
 
-2. Developer friendly and intuitive API
+2. Developer friendly and intuitive [API](https://winkjs.org/wink-nlp/getting-started.html)
 
-3. Built-in API to aid text visualization
+3. Built-in [API](https://winkjs.org/wink-nlp/visualizing-markup.html) to aid [text visualization](https://observablehq.com/@winkjs/how-to-perform-sentiment-analysis?collection=@winkjs/winknlp-recipes)
 
 4. Easy information extraction from raw text
 
-5. Extensive text processing features such as bag-of-words, frequency table, stop word removal, readability statistics computation and many more.
+5. Extensive [text processing features](https://winkjs.org/wink-nlp/its-as-helper.html) such as bag-of-words, frequency table, stop word removal, readability statistics computation and many more.
 
-6. Pre-trained models with sizes starting from <3MB onwards
+6. Pre-trained [language models](https://winkjs.org/wink-nlp/language-models.html) with sizes starting from <3MB onwards
 
-7. BM25-based vectorizer
+7. [BM25-based vectorizer](https://winkjs.org/wink-nlp/bm25-vectorizer.html)
 
-8. Multiple similarity methods
+8. Multiple [similarity](https://winkjs.org/wink-nlp/similarity.html) methods
 
 9. Word vector integration
 
-10. Comprehensive NLP pipeline covering tokenization, sentence boundary detection, negation handling, sentiment analysis, part-of-speech (pos) tagging, lemmatization, named entity extraction, custom entities detection and pattern matching
+10. Comprehensive [NLP pipeline](https://winkjs.org/wink-nlp/processing-pipeline.html) covering tokenization, sentence boundary detection, negation handling, sentiment analysis, part-of-speech (pos) tagging, lemmatization, named entity extraction, custom entities detection and pattern matching
 
-11. No external dependencies.
+11. No external dependencies
 
-12. Runs on web browsers
+12. [Runs on web browsers](https://winkjs.org/wink-nlp/wink-nlp-in-browsers.html).
 
 
 ## Installation
@@ -57,7 +57,7 @@ node -e "require( 'wink-nlp/models/install' )" wink-eng-lite-model
 ```
 
 ### How to install for Web Browser
-If you’re using winkNLP in the browser use the [wink-eng-lite-web-model](https://www.npmjs.com/package/wink-eng-lite-web-model) instead. Learn about its installation and usage in our [guide to using winkNLP in the browser](https://winkjs.org/wink-nlp/how-to-run-wink-nlp-in-browser.html).
+If you’re using winkNLP in the browser use the [wink-eng-lite-web-model](https://www.npmjs.com/package/wink-eng-lite-web-model) instead. Learn about its installation and usage in our [guide to using winkNLP in the browser](https://winkjs.org/wink-nlp/wink-nlp-in-browsers.html).
 
 ## Getting Started
 The "Hello World!" in winkNLP is given below: