Ketul Parikh

Ketul Parikh

Project Trainee

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location of Ketul ParikhAhmedabad, Gujarat, India

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  • Timeline

  • About me

    DevOps Engineer | Backend Developer | 2 X AWS | Knowladge seeker | Autodidact | Inquisitive

  • Education

    • LDRP Institute of Technology & Research

      2010 - 2014
      Bachelor of Technology (B.Tech.) Electronics and Communications Engineering

      Activities and Societies: Coordinator at XENESIS - National Level Tech-festival. Volunteer at XENESIS - National Level Tech-festival.

    • Sheth C.M. High School and Higher Secondary School

      2008 - 2010
      Intermediate/+2 (science) AGRICULTURE, AGRICULTURE OPERATIONS, AND RELATED SCIENCES
    • Mount Carmel High School, Gandhinagar ,Gujarat

      1996 - 2008
      Schooling schooling

      Activities and Societies: - Drawing competition - Dance participation -

    • Dhirubhai Ambani Institute of Information and Communication Technology

      2014 - 2016
      Master of Technology (M.Tech.) Machine Intelligence
  • Experience

    • Embitech

      Jul 2013 - Apr 2014
      Project Trainee

      -To provide best sort of vehicle to handy‐cap people. Apart from physical movement they can move wheel chair by speaking few words. Made the sample model,operated on 12 volts DC power supply- Analysed the integrated potential of ICs and sensors controlled by PIC16F877.- Developed a deep understanding of the Vocal command technology and its conversion to electrical signals.- Undertook the application of Easy Voice Recognize Module to convert human voice to electrical signals.- Familiarized with the ISIS Professional 7 Proteus tool which served the base of the entire project idea.- Successfully developed VOICE CONTROLLED WHEELCHAIR with two modes of the application.- Was awarded the highest ‘AA’ grade by Gujarat Technological University for the project. Show less

    • U

      Aug 2014 - Jun 2016

      Title: Object recognition Using Deep Neural Network (DNN)Description: Given an image which has a single object, use Deep Neural Network approach to recognizing the object. Our goal is to learn the object model using the large dataset in an unsupervised way. We then obtain the features of labeled objects using this model. A supervised training approach is then used to solve the classification problem.To do so, I have done some prerequisites and introductory work:a) Supervised learning - Regression models and neural network on IRIS and WINE dataset.b) Unsupervised learning - Implemented Sparse Auto-encoders on MNIST and CIFAR dataset.c) Train an auto-encoder for estimating a Super-resolved image from the LR-HR dataset.d) Image Inpainting using Sparse Auto - encoder.e) For pre-training network implemented Restricted Boltzmann Machine (RBM).f) Implemented leNet-5 Convolutional Neural Network.g) Studied and implemented major UFLDL exercises. Show less

      • Researcher

        May 2015 - Jun 2016
      • Teaching Assistant

        Aug 2014 - Jun 2016
    • PoshaQ

      Jul 2016 - Jun 2021

      • Directed a team specializing in advanced attribute and garment size detection.• Implemented a dynamic model refinement and deployment pipeline, accommodating weekly data updates.• Crafted a customized pipeline to generate choice-based attributes based on detected poses, colors, and garments,in line with client requirements using Python and MongoDB.• Took the lead in developing internal payment management software, leveraging Node.js. • Developing CV-based attribute (Color) classification for further converting input images to a specific color.• Implemented CV-based attribute detection to eliminate shadows, adjust skin tones, and enhance background.• Collaborated with the QC team to create a correction dashboard for client attribute adjustments.• Successfully integrated with Google Cloud services for enhanced functionality and performance.

      • Product Lead

        Aug 2018 - Jun 2021
      • Data Scientist

        Jul 2016 - Jun 2021
    • Ventuno Technologies (P) Ltd

      Dec 2020 - Jul 2021
      Back End Developer

      Worked as a backend developer.• Technology Used: Python, Django, Swagger, Postman• Developed REST API for OTT platform configuration• Used video encoding and decoding libraries in Python• Developed Unit test cases

    • Sentinel Insights

      Aug 2021 - Nov 2023
      DevOps Tech Lead | Backend Developer

      - Developed Cloud Infrastructure on AWS- Built CI/CD using Jenkins and GitHub actions- Used the following AWS service i. Deployed services on AWS EKS ii. Used AWS S3, SQS, SES, and EFS for our ETL pipeline iii. Used AWS CloudWatch (X-ray, dashboards, metrics, alarms) for the observation and monitoring iv. Used IAM and CloudTrail for Security and Anomaly Detection- Built ETL pipeline using NodeJs- Worked on MongoDB and Snowflake for the data processing

  • Licenses & Certifications

    • AWS Certified Developer – Associate

      Amazon Web Services (AWS)
      Oct 2023
      View certificate certificate
    • Machine Learning - A Case Study Approach

      University of Washington
      Jul 2016
      View certificate certificate
    • R Programming

      The Johns Hopkins University
      Jul 2016
      View certificate certificate
    • AWS Certified Cloud Practitioner

      Amazon Web Services (AWS)
      Oct 2023
      View certificate certificate
    • Programming for Everybody (Getting Started with Python)

      University of Michigan
      Jul 2016
      View certificate certificate
    • Regression Model

      The Johns Hopkins University
      Jun 2016
      View certificate certificate
    • HashiCorp Certified: Terraform Associate (003)

      HashiCorp
      Dec 2023
      View certificate certificate
    • Neural Networks and Deep Learning

      DeepLearning.AI
      Aug 2018
      View certificate certificate
    • German Language

      DUALINGO
      Nov 2016
    • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

      DeepLearning.AI
      Nov 2019
      View certificate certificate
    • Front-End Web UI Frameworks and Tools: Bootstrap 4

      The Hong Kong University of Science and Technology
      Sept 2017
      View certificate certificate