Sagar S. Profile

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$10 USD / 시간

faridabad,

india

$10 USD / 시간

현지시간은 12:17 AM입니다

5월 29, 2018에 가입했습니다

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Sagar S.

@sagarr16

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(0 건의 리뷰)

0.0

$10 USD / 시간

faridabad,

india

$10 USD / 시간

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재고용률

Python Developer | Web Developer

I am a Python Developer having 3 years of experience. I have expertise in Web Development using Python frameworks like Flask and Django. Further, I specialize in Web Scrapping/Crawling and Automation. I have worked as a Google Summer of Code 2019 Student Developer as well as a Research Intern at IIIT Hyderabad. I have mentored various projects and have also helped people learn and improve their coding skills. I promise only the top quality work, fast turnaround and continuous revisions till your satisfaction. I provide the following services: - Web Scraping, Web Crawling, Data Extraction, Automation - Web Development, API Development - Python Programming Github:- [login to view URL] LinkedIn:- [login to view URL] Ready to offer my expertise with high-quality work and 100% satisfaction! Feel free to get in touch for an initial consultation.

Python Developers 분야의 전체 프리랜서 확인 (대상 국가: India)

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포트폴리오

6010474

This project is very near to me and took many days to study completely the literature and also write the Working Notes. An end to end Language-Independent Deep Learning model built using Keras to predict the Named Entity for Indian Languages. The model makes use of the different contextual information of the words along with the Word-Level and Character-Level features that are helpful in predicting the various Named Entity Classes. No domain-specific knowledge and no handcrafted rules of any sort to attain good results. We used 2CNN+LSTM model consisting of CNN as the character-level encoder, CNN as the word-level encoder and BiLSTM as the Tag Decoder.

Github Repo Link:- https://github.com/sagar-sehgal/Named-Entity-Recognition

Named Entity Recognition(NER) for Indian Languages

This is a web portal that consists of a database of all the tutorials of various technologies. Here a user can visit and view the various tutorials of various technologies. A user upvotes the tutorials if he likes any of them. Then these tutorials are shown according to upvotes. Further filters can be used to filter the tutorials on the basis of price, Video Tutorial/ Reading Tutorial and according to the level of difficulty.

Github Repo Link:- https://github.com/sagar-sehgal/Cors

Cors

This project is also very close to my heart and it took a complete semester to make a full-fledged freelancing platform. This project is a web portal built using Django to connect Freelancer to the employers (people who want to get the work done). Projects are added by the employer and then tasks are also added for each project. Then acc. to the skill of a freelancer the tasks are shown to a freelancer in his feed. The employer can select a freelancer for each of the tasks and all of the applicants would be notified about their acceptance and rejection. Further, the freelancer and the employer can rate each other, thus leading to a total rating of a user.

Github Repo Link:- https://github.com/sagar-sehgal/FreelancingIIITS

Freelancing Portal

This project, even though not a big one is very close to me as it was done as a freelancing task and took a few sleepless nights to complete the project. A system which would recommend songs to a user based emotion of the person determined by chit-chatting with the user using a Chit-Chat Chatbot. IBM Watson's emotional API was used to determine the emotion of every response from the user. The response from the user, along with its emotion is sent to the pre-trained chit-chat chatbot model Cake-Chat. Also based on the emotion of the conversation the songs are recommended to the user based on the annotations from `last.fm` the dataset in Million Song Dataset.

Github Repo Link:- https://github.com/sagar-sehgal/Chatbot_Song_Recommender

Chatbot Song Recommender

This project was built using Lucene in Java. In this project, I built a retrieval system on the Indian Monuments. A small dataset for the images of monuments and their corresponding text (small description of that monument). Monuments and their documents were indexed with their Soundex codes. Since it is difficult to write the correct spelling of monuments and its location, the monuments are indexed and more weight is given to the name of the document and less to its description. Correct monuments are retrieved using the Soundex code of the query given by the user.

Github Repo Link:- https://github.com/sagar-sehgal/MonumentSearch

Indian Historic Monument Search Engine

It was a part of the Google Summer of Code 2019 project. The project was to build the Interface for Query Generator for CQP4RDF which is a Multi-Layer Annotation Query Tool. CQP4RDF is a tool which is capable to query over a corpus with multiple layers of annotated data.

For eg:-
Consider POS Tag for every word in a sentence. This is just one layer of annotation which we have. Now if I index the words also in a sentence. Like the order in which they occur in a sentence. The first word would be having an ID of 1, followed by 2 and so on. So, if I have all of these annotations on the same data, like the id, word, POS Tag, this can be said to be Multi-Layer annotated data.
CQP4RDF is used to query this type of data.
So, for the sentence like- "Delhi is the capital of India," we can have a query like
w1: [ ID="1"] & w2: [ID="2"]
And this query would retrieve all the relevant sentences from the corpus.

Github Repo Link:- https://github.com/acoli-rep

Multi-Layer Annotation Query Tool

6010474

Named Entity Recognition(NER) for Indian Languages

Cors

Freelancing Portal

Chatbot Song Recommender

Indian Historic Monument Search Engine

Multi-Layer Annotation Query Tool

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경력

Google Summer of Code

5월 2019 - 9월 2019 (4 , 1 )

https://summerofcode.withgoogle.com/archive/2019/projects/6692203190026240/

AIMA Code

12월 2018 - 7월 2019 (7 , 1 )

https://github.com/aimacode/aima-python/pulls?utf8=%E2%9C%93&q=author%3Asagar-sehgal

Learn IT Girl

3월 2019 - 6월 2019 (3 , 1 )

https://www.credential.net/1899022e-25ea-42f1-8184-9a597776b886

교육

Bachelor in Technology

Indian Institute of Information Technology,

India

2016 - 2020

(4 )

출판물

A Named Entity Recognition System for Indian Languages

Forum for Information Retrieval Evaluation

An end to end Language-Independent Deep Learning model to predict the Named Entity for Indian Languages. The model makes use of the different contextual information of the words along with the Word-Level and Character-Level features that are helpful in predicting the various Named Entity Classes. No domain-specific knowledge and no handcrafted rules of any sort to attain good results.