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ArpitaChatterjee/README.md

Hello, I'm Arpita Chatterjee

Arpita

I'm a Software Engineer.

  • 🌱 I am a Software Engineer with almost 4 years of experience building and improving automation frameworks, backend and API validation systems, and CI/CD pipelines for high-traffic consumer products.

  • 📫 I have a strong track record of raising test coverage to over 86%, improving build stability to 90%, and speeding up releases for iOS, Android, and web platforms.

  • 🔭 My technical skills include Java, Appium, Selenium, TestNG, Rest Apis, Python, SQL, cloud-based test infrastructure, and DevOps tools. I have worked on production systems at a global security product company.

  • 🥅 Always motivated to learn New Technologies and Contribute more to Open Source projects .

    Core Technical Skills

Connect with me:

Arpita Arpita | LinkedIn Arpita | Instagram


Willing to collaborate on something intresting, Hit me up at any of my socials !!

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  1. Routine-Analysis-of-a-Comedian Routine-Analysis-of-a-Comedian Public

    Build a dataset using the transcript for the 10 popular comedians, using web scrapping, and applied various NLP techniques like sentiment analysis, topic modeling, text generation, and recommended …

    Jupyter Notebook 1

  2. Covid-19-Tracker-with-VoiceAssistant Covid-19-Tracker-with-VoiceAssistant Public

    Built a Covid-19 tracker in python, where data of total no. of cases, total no. of deaths, total no. of recovered cases of all the countries was scrapped and an API was generated.With the help of s…

    Python 5

  3. Book-Recommendation-System Book-Recommendation-System Public

    Build a user-item rating matrix; based on which correlation between each item and the user, was determined and with the help of 'cosine' similarity metrics, user-based and item-based recommendation…

    Jupyter Notebook 1

  4. Movie-Review-Sentiment-Analysis Movie-Review-Sentiment-Analysis Public

    Text classification model which trains a recurrent neural network(RNN) on the large movie review dataset for sentiment analysis.

    Jupyter Notebook 1

  5. Biometric-Attendance Biometric-Attendance Public

    Built a Facial Recognition Model in Python. Used Face Recognition library, to detect the face locations and their encoding in the training dataset. Compared faces with the test dataset, using the f…

    Jupyter Notebook 1