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DSC IEM - rake_new2 - Reports #13

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# Developer - Winter of Code 2020
# Malayaj Rath
### DSC IEM : rake_new2

The Projects I was working on are [Automatic Spell Check](https://github.com/BALaka-18/rake_new2/tree/feature-addition/feature_enhancements/malayajrath_feature_SpellCheck) & [Topic Modelling](https://github.com/BALaka-18/rake_new2/tree/feature-addition/feature_enhancements/malayajrath_feature_TopicModeling) which belongs to [Rake_new2](https://github.com/BALaka-18/rake_new2/tree/master) application which is a Rapid Automatic Keyword Extraction library .

Automatic Spell Check help in autocorrection of the misspelt word .

Topic Modelling help to find relevant topics of a given statement or paragraph.

My work in this winter increased the features and accuracy of the library .

I am [Malayaj Rath](https://github.com/malayaj2000) an undergraduate student from [NIT ROURKELA](https://www.nitrkl.ac.in/) as part of [Winter of Code](https://winterofcode.com/).

This project was mentored by - [Balaka Biswas](https://github.com/BALaka-18)


# Contributions

14 [commits](https://github.com/BALaka-18/rake_new2/commits/feature-addition)

### 1. Automatic Spell Check
In this task ,I was responsible for making a automatic spell checking feature when enabled it correct misspelt words .

It avoid names and other similar catagories .

All code was written in sync with rake_new2 tech stack and style.

[#34](https://github.com/BALaka-18/rake_new2/pull/34) [Automatic Spell Check](https://github.com/BALaka-18/rake_new2/tree/feature-addition/feature_enhancements/malayajrath_feature_SpellCheck)

### 2.Topic Modelling
In this task, I was responsible for making a Topic Modelling feature when enabled
and specified number of topics it find relevant topics .

All code was written in sync with rake_new2 tech stack and style.

[#34](https://github.com/BALaka-18/rake_new2/pull/34) [Topic Modelling](https://github.com/BALaka-18/rake_new2/tree/feature-addition/feature_enhancements/malayajrath_feature_TopicModeling)

# New Features
1. Automatic Spell Check

It is a auto spell check feature when enabled it correct misspelt words .

It internally uses Textblob and Spacy library to identify and correct all necessary error.

2. Topic Modelling

It topic extracting feature When enabled and specified number of topics it find relevant topics .

It internally uses Sklearn's LDA(latent dirichlet allocation) to find topics.

Here are some of [my PRs](https://github.com/BALaka-18/rake_new2/pull/34)

# Future Scope
I hope my work on Automatic Spell Check & Topic Modelling help to improve the rake_new2 library.

Both of the feature could be helpful in various official purposes and also help rest all existing features.

Both Automatic Spell Check & Topic Modelling can be really helpful for finding Sentiment of Statements which is really important now a days .

I hope my contributions will help other future contributions.

I'm looking forward to contribute more to this library and improve the main keyword extractions algorithm

# Overall Experience
I had a awesome winter ,2020 working with the team rake_new2 under the program [Winter of Codes](https://winterofcode.com/),2020. It was a very exciting and great
experience working in such a collaborative and supportive environment .

I'm thankful to my mentor & creator of [rake_new2](https://github.com/BALaka-18/rake_new2/tree/master) - [Balaka Biswas](https://github.com/BALaka-18) for guiding me through all problems and going through my PR.

WoC & rake_new2 will remain a memorable experience for me.
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# Developer - Winter of Code 2020
# Sayantan Dasgupta
### DSC IEM : rake_new2

The project I had worked on was [Sentiment Analysis](https://github.com/BALaka-18/rake_new2/tree/feature-addition/feature_enhancements/sayantandasgupta_feature_sentiment-analysis).

This feature analyzes the sentiment of the piece of text as provided by the user.

My work in this project has added a sentiment analysis feature to the library [rake_new2](https://github.com/BALaka-18/rake_new2).

I am [Sayantan Dasgupta](https://github.com/Arka2001) from [IEM, Kolkata](https://iem.edu.in) as part of [Winter of Code](https://winterofcode.com).

This project was mentored by - [Balaka Biswas](https://github.com/BALaka-18)
# Contributions
- 1. ###Sentiment Analysis
In this task, I was responsible for provideing a sentiment analysis feature to the project.
It only requires a large corpus of text to work on.
All code was written in sync with the rake_new2 tech stack and styles.
[#36](https://github.com/BALaka-18/rake_new2/pull/36) [Sentiment Analysis Initial](https://github.com/BALaka-18/rake_new2/tree/feature-addition/feature_enhancements/sayantandasgupta_feature_sentiment-analysis)

# New Features
1. Sentiment Analysis

It is an automatic sentiment analyzer which analyzes the sentiment of any piece of text provided by the user.

Here are some of [my PRs](https://github.com/BALaka-18/rake_new2/pull/36)

# Future Scope
I hope my contribution to the rake_new2 library has helped in its overall functionalities and efficiency.

I would like to add some more features to this library like a language translator.

The feature that I have added would be very helpful for industrial purposes because it is very important to learn about the sentiments of the general public.

I am looking forward to contributing more to this library.

# Overall Experience
I have had a great winter. With the WoC 2020, I had a great time in learning something new and also to start contribute to industry level projects. I have gained quite a lot of confidence after the completion of this project. My mentor, Balaka Biswas, was most helpful and cleared all of my doubts with patience. I want to thank her heartily because my project would have not been completed if it wasn't for her guidance.

WoC would remain a memorable experience for me.