Product utilized AWS resources listed out and developed dashboard for that

 Staging, Product environment creation for product

 Various utility tasks were done for the project

 Android App was developed with small utility

Prepared System monitoring controller scripts using linux commands

AWS automatic resource allocation (Auto attach, detach, mount, unmount, etc.) scripts

AWS effective resource selection (Best region to keep codes, best instance for better performance, etc.)

Log rotate to clean up

AWS customized bill generator was developed

Automatic Code sync between 4 regions repositories (Github) and get notification of that with updated

code percentage

Handled various REST operations and recovered data from there

Applied multiple way of regular expressions to collect data points

Collect data points from various retailer websites

Handled various REST operations and recovered data from there

Applied multiple way of regular expressions to collect data points

Collected data points from various amazon api (asin info,oxylabs,asinator)

Architected overall process of this project

Text Classification has been done for amazon titles, brand, manufactures, breadcrumb, productgroup,

category, description, feature

NLP Pre-processing has done for amazon texts

Various machine learning algorithms were analyzed and implemented

Similar titles were grouped using elastic search

Google translation, matecate translation api were analyzed and implemented

NLP Preprocessing, Classification, Grouping

Vector Space Model, Dimension reductions(Tf-Idf, LSI), Text similarity algorithms implemented

Worked on Semantic text similarity Word2Vec, FastText, GloveVec, Doc2Vec, WordNet

Wored on Character based similarity – Fuzzywuzzy, Jaro, Jaro-Winkler, Levenshtein, Damerau–

Levenshtein, Sorensen, Ngram

Worked on term-based similarity – Cosine similarity, Jaccard Similarty

Model built, created index from corpus, queried to collected similar amazon products from model instantly

Banking Insurance Prediction, Fintech platform api latency prediction , Product Recommendations

Backend Setup Prepared using AWS Components for Adjuster Product

GraphQL setup was prepared