Update README.md

Author: Muhammad Haseeb

README.md

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 # Python-Implementation-of-LSA
-A Jupyter notebook on implementation of Latent Semantic Analysis (A Topic Modelling Algorithm) in python.
+
+Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the
+contextual-usage meaning of words by statistical computations applied to a large corpus of
+text (Landauer and Dumais, 1997). The underlying idea is that the aggregate of all the word
+contexts in which a given word does and does not appear provides a set of mutual
+constraints that largely determines the similarity of meaning of words and sets of words to
+each other. The adequacy of LSA’s reflection of human knowledge has been established in
+a variety of ways. For example, its scores overlap those of humans on standard vocabulary
+and subject matter tests; it mimics human word sorting and category judgments; it simulates
+word–word and passage–word lexical priming data; and, as reported in 3 following articles
+in this issue, it accurately estimates passage coherence, learnability of passages by
+individual students, and the quality and quantity of knowledge contained in an essay.
+
+
+### Prerequisites
+
+Things reuired<br>
+1. Jupyter Notebook
+2. Python
+3. Gensim
+
+## Getting Started
+
+To use this Code just download the repository & open it up in Jupyter Notebook. The code is ready for your next use, So what are 
+you wating for? Start creating something awesome! Good Luck!
+
+
+## Built With
+
+* [Gensim](https://radimrehurek.com/gensim/index.html) - The main Library used
+* [Python](https://www.python.org/) - Programming Language used
+* [Jupyter Notebook](http://jupyter.org/) - A web based coding enviorment
+
+
+## Contributing
+
+Feel free to submit pull requests to me.
+
+
+## Authors
+
+* **Muhammad Haseeb** - *Initial work* - [Muhammad Haseeb](https://github.com/iam-mhaseeb)
+
+
+## License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details