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Hi πŸ‘‹, I'm Pratik Barjatiya

Pratik Barjatiya

Passionate professional and love to deep dive in data.

πŸ‘‹ Hi there! I'm Pratik Barjatya, a passionate data engineer and machine learning enthusiast. I enjoy working with big data technologies and building scalable data pipelines to extract insights from massive datasets.

πŸš€ As a tech enthusiast, I love exploring emerging technologies and leveraging them to solve real-world challenges. From data ingestion and processing to designing efficient data architectures, I thrive on turning complex data problems into actionable solutions.

πŸ’» My GitHub repositories showcase my work in data engineering, where I share projects, code snippets, and best practices related to data processing, ETL, and data integration. Feel free to explore and collaborate on these projectsβ€”I'm always open to new ideas and collaborations!

πŸ“š When I'm not coding or tinkering with data, you'll find me diving into books and articles on the latest trends in data engineering and machine learning. I believe in the power of continuous learning and enjoy staying up-to-date with the ever-evolving tech landscape.

By Nature, I am keen to explore untapped areas, research and build applications. Willing to learn and being available as a mentor for the one who wants to explore this field.

Strong believer in giving back to community and running Learn-On-Go

Knowledge sharing space Data Engineering

My portfolio is a representation of all that I have learned and accomplished as a Techie student. The articles and projects you will see in this portfolio show how my knowledge and experience have evolved over time.

Checkout my blog - https://pratikbarjatya.medium.com Visit my website - https://pratikbarjatya.github.io

Connect with me:

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Skills I have

  • Data Engineering - Python | PySpark | NiFi | Airflow
  • Machine Learning
  • ELK Stack
  • NLP Deep Learning
  • Statistics
  • AWS EMR, EC2, S3, RedShift, Athena, Glue, Sagemaker
  • Data Visualisation
  • SQL, NoSQL, MySQL
  • Tableau

Articles I have written

Data Engineering

Personal Finance & Heatlh

Software Testing and Quality Engineering

Connect with me

I am currently looking for new opportunities. My inbox is always open, whether you have a question or just want to say hi, you can always connect with me.

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GitHub Statistics


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Top Langs

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⚑ Technologies I use


Python

Spark

Jupyter

TensorFlow

Pytorch

Scikit Learn

FastAPI

Docker

Pratik Barjatiya's Projects

sample-code icon sample-code

appium sample code (dotnet, java, node, perl, php, python, ruby, etc.)

scott icon scott

Never debug a test again: Detailed failure reports and hassle free assertions for Java tests - Power Asserts for Java

scriptingstuff icon scriptingstuff

This presents basic stuff I learned while involved in scripting

selenium-foundation icon selenium-foundation

Selenium Foundation is an automation framework designed to extend and enhance the capabilities provided by Selenium (WebDriver).

seleniumtestsframework icon seleniumtestsframework

STF is a webdriver based test automation library which generates comprehensible tests reports comparable to BDD framework, and yet better since no extra test steps / configuration are required. Not just this, STF has tons of other useful features described at -

sentiment-analysis-on-hindi-reviews icon sentiment-analysis-on-hindi-reviews

We have used 250 sentences of movie reviews available for research from IIT bombay and also crawled and manually annotated 750 reviews from jagran.com, In total 1000 reviews. After preprocessing the dataset, We generate the featureset as a vector-based approach using Term frequency, tfidf for unigrams and bigrams. Then we used three approaches to predict the sentiment of a review. Approaches used are Resource based, In-language semantic analysis and Machine Translation based semantic analysis.

serenity-core icon serenity-core

Serenity (previously known as 'Thucydides') is a library designed to make writing automated acceptance tests easier, and more fun.

sometime icon sometime

A BurpSuite plugin to detect Same Origin Method Execution vulnerabilities

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