aritra31,Aritra Ray,github

Hey there, <𝚌𝚘𝚍𝚎𝚛𝚜/>! I'm Aritra.

I am from Kolkata, West Bengal and currently doing my B.Tech in CSE from Institute of Engineering and Management, Kolkata. "Learning on the go" keeps me going on.

👨🏻‍💻 About Me

I’m currently learning Cloud Computing and JavaScript
Exploring new technologies and developing software solutions
Cloud Enthusiast
Machine Learning and Artificial Intelligence draws me.
Content writing passes me bliss
Playing synthesizer and sketching as hobbies/side hustles.
Coffee be my stress-buster

🛠 Tech Stack

Talk to me about...

Backend development using Django
Front-end development using HTML, Javascript,CSS,Bootstrap
Platforms like Android Studio | PyCharm | Visual Studio code | Git | Vscode
Android application development using Flutter(Still learning)
Creating scalable cloud architecture using AWS Cloud
Solving Data structure and algorithm questions in C++ and Python

🤝🏻 Lookin' forward to connect with you!

Aritra Ray's Projects

coding-interview-university

A complete computer science study plan to become a software engineer.

css-animations-hacktober

css files for designing attractive webpages

hacktoberfest-2021

A repository for Hacktober Fest contributions. Everyone is welcome. Fork away!

hacktoberfest_dsa_2021

Submit Just 4 PRs this month to earn SWAGS and Tshirts🔥.

thealgorithms

This contains whatever you need to study about Algos...

In today’s era, the impact of social networking media such as Facebook, Google Plus, YouTube, Blogs, and Twitter is increasing rapidly day by day. Millions of people are connected with each other on social networking sites and express their sentiments and opinions through tweets, and comments. This motivates the automatic mining and classification of views, emotions, opinions, and feelings of people on social networking websites. Sentiment analysis is the method of automatic mining of the sentiments or opinions of a text unit. In today’s world, people express their feelings, opinions on twitter about certain things i.e. event, topic or person. The proposed work deals with mining sentiments or emotions of tweets using Support Vector Machine. Unigram and TF-IDF are used as feature extractors and the performance of the proposed approach is measured in terms of accuracy, precision, recall, and f-measure.

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