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Hi, Myself Yash ๐Ÿ‘‹

  • Automation Enthusiast ๐ŸŒŸ
  • RPA (Robotic Process Automation) Practioner ๐Ÿค–
  • AI and DevOps Aspirant ๐Ÿš€

Who am I?

I am someone who likes to interact with multiple technologies and to be a key player in the midst of all the critical tasks that are being handled in projects. My conviction is that we can work, practice, and update our knowledge on our own, but the true essence of shaping a good career only comes through problem-solving at an industrial stage of projects. My work on GitHub are simply my experiments to understand the technologies of my interests.

My Skillset

  • Languages: Java, Python, Shell script, JavaScript, HTML, CSS, Bootstrap, C#, JSON, XML, SQL, Git
  • Technologies & Tools: Ui-Path, MySQL, Redis, MongoDB, Docker, Spring Boot, Express-js, Node-js, AJAX-jQuery, Eclipse, Postman, Git, Virtual Box, Intellibot, Automation Anywhere, Databricks cluster, Google-Colab, PySpark ML-lib, ServiceNow APIs, Py-torch, Jira, GitHub
  • Technical Aspects: Object-Oriented Programming, Web-services, Microservices, Containerization, Virtualization, Neural Net, Big-data, REST APIs, RPA, RE-Framework (Ui-Path), IQ-bots, Meta-bots, Artificial-Intelligence

My 2 cents on Automation ๐Ÿ˜„


It not that simple, like some piece of cake. You will only have dimples, until you start to bake.

There is a lot of work for automation's sake. Don't forget the ones who built it without break. Because its automation's job to make, make & make. But it only exists for humans to take.

โ€” Yash (Relax, didn't borrow it from GPT ๐Ÿ˜‰:)

Iโ€™m currently working on ๐Ÿ”ญ

  • Jobs๐Ÿ’ผ - I am looking for roles in the domain of RPA as well as software development, backend is my favourite
  • Learning๐ŸŒฑ - Good frameworks for web-dev and trying different applications of AI/ML
  • Personal projects๐Ÿ“• - Something magical is brewing in my brain๐Ÿง  regarding a music application ๐ŸŽต๐ŸŽป๐ŸŽน and a cool DSA project๐Ÿ’ก

Education

Institutions Achievements
University of Texas at Dallas Master of Science in Computer Science (Specialization - Intelligent Systems)
Vellore Institute of Technology Bachelor of Technology in Computer Science and Engineering

Where did I work?

Organization Position/Role
Dechert LLP RPA Developer - Enterprise Applications Team
Tata Consultancy Services (TCS) Systems Engineer - RPA (Robotic Process Automation) Team
Poly (now acquired by HP - Hewlett Packard) RPA (Robotic Process Automation) Intern - Enterprise Application Team
Tata Consultancy Services (TCS) Software Developement (Microservices) Intern - Backend and API Team

How to reach me ๐Ÿ“ž

Yash Vijaynarayan Gupta's Projects

ai_graph_search icon ai_graph_search

AI related graph search algorithms with step-by-step implementation as well as comparison between different methods for cliff-walker problem.

ai_mobilenet_image-classification icon ai_mobilenet_image-classification

AI based image classification inspired MobileNet V2 architecture by implementing changes in base architecture and details about using it as a quick response model (proposition) for rapid application as well as comparing it with other models for the same application.

big_data_project_us-airlines_tweet_processing_and_analysis icon big_data_project_us-airlines_tweet_processing_and_analysis

Big data application of Machine Learning concepts for sentiment classification of US Airlines tweets. The focus is on the usage of pyspark libraries (ml-lib) on big data to solve a problem using Machine Learning algorithms and not about the choice of algorithm used in the ML model creation. It also involves data pre-processing using NLP techniques, cross-validation and parameter-grid builder.

ml_usa_pollution_prediction icon ml_usa_pollution_prediction

LSTM (RNN) analysis of Time Series data (pollutant metrics) of 4 different pollutants (NO2, SO2, CO, O3) over US data.

mlops_collaborative_ml_with_homomorphic_encryption icon mlops_collaborative_ml_with_homomorphic_encryption

Collaborative Machine Learning approach to train a mode that classifies a person as smoker or non-smoker based on the user data. The distributed approach of training is done with secure model transmissions to central cloud location where Amazon EC2 instance aggregates the new model based on new training received in Homomorphically Encrypted forms

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