Ashish Vishwakarma

Tata Consultancy Services, Mumbai.

QA Automation Engineer • April, 2021 — Present

QA Automation Engineer, Worked on Manual and Automation for Websites — mobile (Web — Native) applications [Health care domain] using Python, Selenium, Appium, BrowserStack.

QA Automation Mobile Apps & Website testing

Mobile apps [iOS — Android]automation testing using Python, Appium, Selenium WebDriver, Pytest, Pytest-BDD, Pandas, Open-cv

Automated more than 50 apps in Helath Care domain both public and private

Worked in Behavior Driven Development (BDD) by writing Gherkin language using cucumber tools, developed Scenarios, features, Step definitions in Page Object Model(POM)

Configured Selenium, Appium, Pytest and created automation scripts in Python

Documented using Jira with TestRail integration>

Atharva College of Engineering, Mumbai Univserity, Maharshtra, India

Bachelor of Electronics Engineering • 2016 — 2020

Build an Audio Classifier for birds species identification

Primary Developer • 2019 — Present

Build an audio classfier using Pytorch. Dealt and applied analysis on Audio Data using Python packages librosa, PyDub. Audio signal varies in frequencies at different sampling rate and their features was extracted using Mel-Spectogram.

• Scraped audio data from kaggle api and xeno-canto.org. Performed EDA on Data and Converted raw audio data into .png & .npy files
• Build an Sound Event Detection model using Pytorch and Pytorch Lightning

Web Scraping, Python script for fetching news headlines and articles

• Feb 2022 — Present

A web-scraping python script to fetch and save news headlines and articles using BeatuifulSoup, requests and pandas. Scraped news articles from TOI archive links. Saved those archive links in pandas-csv file.

News Summarization and deployed model using FastApi

Primary Developer • Feb 2022

A well-summarized news are crucial in delivering the main point of the news article to its potential readers so build and deployed an pre-trained model using Pytorch and hugging face, Fine-tuned pre-trained model using Pytorch and hugging face on custom dataset. Save the trained model in ONNX runtime for inference,Used FastApi with saved ONNX model for API inference

Technical Skills

Python

Pytest, Selenium, Appium, Pytest-bdd

Numpy, Pandas, Matplotlib, Open-cv, PIL-image

Tensorflow, Keras, Pytorch, Pytorch Lightning, FastApi

Java

Selenium, Appium, WebdriverManager, Gherkins

Courses

• Coursera :- Neural Networks and Deep Learning (TRYG2KR4L7MX)
• Linkedin learning :- SQL Essential Training

Workshop and Traning

Larsen & Toubor Corporate:- Technology & Engineering Academy Training on Power Electronics and PLC (3 Days)

• Reading - Fav author - Franz Kafka.
• Video Games - Valorant, League of Legends - Irelia main.
• Gym, Looks Skinny but tries my best to be Healthy and fit.