Kajal Kankariya

To work in a challenging environment where I can put my best efforts and knowledge to reach the respective company's goals and objectives

• Secured 10th Rank in Pune University in final year among all students (of all the branches) from all colleges affiliated to the University.
• Secured 2nd Rank in Pune University in the third year in the computer engineering branch and 4th among all students (of all the branches) from all colleges affiliated to the University.
• Secured 1st Rank in the final year in college in class (strength 353)
• Topped 4 courses in class: Data Mining and Warehousing, Machine Learning, Soft Computing and Optimization, and Algorithm Information and Cyber Security
• Secured 1st Rank in the third year in college in class (strength 353)
• Topped 2 courses in the third year: Software Modelling and Design, and Web Technology
• Won 'The Best Outgoing Student Award' in my college among 500 students.
• Topped 'Computer Graphics' & 'Principles of Programming Language' in the 2nd year.
• Secured 8th Rank in the first year in the undergraduate program among 500 students.
• Secured 1st Rank in grade XII board exam in college with a percentage of 94.6%
• Secured 3rd Rank in grade X state board examination - in school with an aggregate 96.2%

Text Summarization using Seq2Seq model

Natural Language Processing (NLP)-based summarization techniques address this challenge by automatically generating succinct and coherent summaries. A Seq2Seq model, applicable to various sequential information tasks such as sentiment classification, neural machine translation, and named entity recognition, proves beneficial in this context. News articles, with their rich grammar and vocabulary, provide valuable insights for model training

• · Melanoma detection using multiclass classification model using a custom convolutional neural network in TensorFlow
• · predict fraudulent credit card transactions with the help of machine learning models
• · Identifying the diseases and predicted treatment using a custom NER
• Automatically classify customer complaints based on the products and services that the ticket mentions using NLP
• Prediction of demand for shared bikes using multiple linear regression model
• Lending club case study
• House Price prediction using Advanced Regression

Developed an Intelligent Agro-System with IoT technology, integrating crop prediction and intrusion detection. Utilized Raspberry Pi for control, IR sensors for intrusion detection, and soil moisture/temperature sensors for agricultural monitoring. Implemented automatic and manual modes, with data stored in MySQL and processed on Raspberry Pi. Presented at ICINC-2020 conference.

• Microsoft Azure Fundamentals Exam Prep- AZ 900
• Cloud FinOps
• Security Training - Openssl and Basic of Cryptography
• Certified Kubernetes Administrator
• Cloud Training
• Golang

Date of Birth: 09/13/98

• English
• Hindi
• Marathi

• Drawing
• Painting
• Swimming