This document is a resume for Sayantan Ghosh summarizing his professional experience and qualifications. It outlines his work as a data analyst intern where he conducted machine learning projects on classification algorithms and neural networks. It also details his experience as a Wordpress developer creating websites. His education accomplishments include studying computer science and engineering with a GPA of 9.68. Key skills include proficiency in HTML, CSS, JavaScript, Python, machine learning and data structures.
I am a passionate and hardworking student currently pursuing my Bachelor's degree in Information Technology. My areas of Interest include Software Development, Data Structures and Algorithms, Machine Learning. I am open for full-time Job Opportunities.
I also love creative writing, public speaking, community service and sports.
Looking for an Internship or a working opportunity that proves incentives to learn, explore and enrich skills in the field of Data Science or Software Development.
I am a passionate and hardworking student currently pursuing my Bachelor's degree in Information Technology. My areas of Interest include Software Development, Data Structures and Algorithms, Machine Learning. I am open for full-time Job Opportunities.
I also love creative writing, public speaking, community service and sports.
Looking for an Internship or a working opportunity that proves incentives to learn, explore and enrich skills in the field of Data Science or Software Development.
Looking for an Internship or a working opportunity that proves incentives to learn, explore and enrich skills in the field of Data Science or Software Development.
Data Science enthusiast, performing data analysis and predictive modelling using various machine learning algorithms. Sound knowledge of statistics used to gather insights from data and making data driven decisions.
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Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Sayantan ghosh resume
1. SAYANTAN GHOSH
(+91)9609078275 | gsayantan1999@gmail.com Military Bagan,Kalna,Burdwan,West Bengal
sayantan1999arka.000webhostapp.com | Sghosh1999 | sayantan-ghosh-b16461153
PROFESSIONAL SUMMARY
An academically and commercially astute learner and engineer with a passion for venturing new
concepts on Machine Learning and data analytic s. These interest me just as much crafting my ideas into
canvas with my brushes. I draw and design when I am not busy with my academics. Always enthusiastic
to delve into the unknown; self driven and amicable. I identify myself as a valuable team-player and
problem-solver with effective programming skills and hardworking mentality. Seeking to apply expertise
and extensive experience in working with data on an challenging new role proving my potential with a
growing team.
WORK EXPERIENCE
June’2019 - Present Data Analyst Project Intern
(NIIT,Kolkata)
I. Created a Comparative analysis of Machine Learning Classifier Algorithms
on Kaggle dataset(Titanic disaster Prediction).
II. Worked on developing an Artificial Neural Network for face recognition.
III. Created a digit recognizer using Convolution Neural Networks.
IV. Developed an detailed project report on data exploration,and ML
Classifying Techniques.
Wordpress Developer
(Sidhasadha, Kolkata)
(Link : https://sidhasadha.com/)
I. Worked as a Front-end and Backed developer using content management
system(Word-press).Designed the UI from scratch.
II. Worked on Browser Compatibility and SEO , attractive Navigation system
and mobile compatibility.
Mar’2019 -
Present
2. III. Developed an e-commerce website platform with frequent and fast
WP-Mail setup.
IV. Designed and developed user friendly optimized checkout page that
increased user clicks,and subsequently customer purchase by 20%.
V. Fixed bugs from existing website and implemented enhancements that
significantly improve web functionality and speed.
Internshala Student Partner 12
(Internshala)
I. Help out college peers by make them aware about the latest internships
and training offers and assist them with internships and training related
queries.
II. Conducted workshops/seminars in college, represent it in college society
and organizations.
III. Participated in monthly contests and compete with other ISPs from all
over India.
IV. Participated in monthly learning track events - setup for your learning and
development.
PROJECT WORKS
I. Web Application on Tracing Evolution of living Beings (Hackerearth)
(Link - https://github.com/Sghosh1999/Earth_Evolution_Website) March’2019
Developed a mobile responsive web application to depict the evolution of every living being on earth
through an interactive way.
Created a responsive scrolling timeline with a Wikipedia api based search engine to gather further
information of evolution.
Created a concise application using html5,CSS3,Bootstrap,and JavaScript Api.
II. Banking Probabilistic Model using Artificial Neural Network
(Link - https://github.com/Sghosh1999/ANN-Model) March’2019
A probabilistic model to predict whether a customer will remain in the company or not analyzing several
independent factors using Artificial Neural Network.
Obtained a accuracy of 84.6 % in the final epoch of the model.
It will help for a company to know their customer relations,to improve that and knowing their future
steps.
Dec’2018 -
Mar’2019
3. III. Review Analysis using Natural Language Processing and Naive Bayes Classifier
(Link - https://github.com/Sghosh1999/Natural-Language-Processing)
March’2019
Worked on a data-set of 1000 reviews of a restaurant and cleaned the reviews using nltk.corpus and
re(Regular Expression Operations)library.
Stemmed the reviews and extracted the root words to reduce the complexity of the sparse matrix.
(Every word assigned a column so including tenses can create trouble in our algorithm).
Created Bag Of Words Model to predict the dependent variable(binary outcome) where each
unique word act as a independent variable.
Fitted the training set to Naive Bayes Classifier to get the desired output .
Created confusion matrix and got a 73% accuracy on 200 reviews.
IV. Comparative detailed analysis on ML Classification Algorithms.
March’2019
Worked on the Titanic Dataset and applied Classification Algorithm for Precision Analysis.
Tuned Hyper Parameters for better Accuracy and precision.
Developed an Face Detection Intuition using Open_CV.
Created a detailed data Exploratory Techniques to analyse the dataset more critically and to increase
the accuracy without over fitting.
EDUCATION
Bachelor of Technology(B.Tech) Jul’2017 - Present
Computer Science and Engineering
Kalinga Institute Of Industrial Technology,Bhubaneswar
CGPA(till 3rd
sem): 9.68/10
Higher Secondary Jan’2015 - Feb’2018
Science
Kalna Ambika Mahismardini High School,Kalna,WB
CGPA : 9.26/10
4. SKILLS
HTML CSS Java script
Advanced Advanced Advanced
Wordpress Python Machine Learning
Advanced Advanced Advanced
C Data Structures
Advanced Advanced
ACHIEVEMENTS
I. 3rd
position in #HackBenchers Hackathon among 1654 teams in Hackerearth.
II. Semifinalist (Rank-589) in Artificial Intelligence Contest hosted by TECHGIG.com
III. Shortlisted for a Global business Case Challenge(Go Green in the city 2018) hosted by Schneider Electric.
IV. Secured 17 th Zonal rank and 557 th National Rank in Pathfinder National Talent search Exam.
V. Qualified Google Digital Certified Exam.
VI. Actively participated in codechef, hackerearh contests.