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suwarna93/suwarna93 is a ✨ special ✨ repository because its README.md (this file) appears on your GitHub profile. Here are some ideas to get you started:

  1. Implemented Jenkins CI/CD pipeline integrating tools such as Maven, SonarQube, JFrog, and Kubernetes.

  2. Executed various stages including building, unit testing,Created Docker images , and deploying on the Kubernetes platform. 3)Designed Kubernetes manifest files to align with the development team's requirements. 4)Executed Terraform scripts according to the requirements of the development team, detailing infrastructure components such as VPC, Subnets, EC2 Instances, and Route53.

  3. Implemented triggers using webhooks and scheduled builds to automatically run Jenkins jobs.

  4. Monitored Kubernetes clusters to quickly identify issues such as application crashes and network problems.

  5. Integrated Prometheus with Grafana to send data using PromQL and display charts, graphs, and POD monitoring data on the dashboard.

  6. Dedicated to creating robust and scalable data solutions for real-world challenges.

  7. Collaborative team player with excellent communication and problem-solving skills.

  8. Adaptable and eager to take on new challenges in the dynamic field of DevOps.

  9. Actively engaged in the data science community and open to collaborations and knowledge-sharing.

    Feel free to explore my GitHub repositories for examples of my work and projects. I'm open to connecting and discussing potential opportunities in the field of data science.

suwarna baraskar's Projects

-cyberbully-detection-text-classification- icon -cyberbully-detection-text-classification-

🧾**Description:** This dataset is a collection of datasets from different sources related to the automatic detection of cyber-bullying. The data is from different social media platforms like Kaggle, Twitter, Wikipedia Talk pages, and YouTube. The data contains text and are labeled as bullying or not. The data contains different types of cyber-bullying like hate speech, aggression, insults, and toxicity. You have been provided with the twitter\_parsed tweets dataset, wherein you have to classify whether the tweet is toxic or not. 🧭 **Problem Statement:** You are provided with **twitter\_parsed\_tweets**: you have to perform a step-by-step NLP approach to identify the toxicity of the tweet, and classify the tweet in a binary value.  The target variable is **oh-label** and the evaluation metric is **F1-score**.

-dmsp-particle-precipitate-flux-prediction-mesoscale- icon -dmsp-particle-precipitate-flux-prediction-mesoscale-

particle precipitation data that includes 51 satellite years of Defense Meteorological Satellite Program (DMSP) observations temporally aligned with solar wind and geomagnetic activity data. The new total electron energy flux particle precipitation nowcast model, a neural network called PrecipNet, takes advantage of increased expressive power afforded by ML approaches to appropriately utilize diverse information from the solar wind and geomagnetic activity and, importantly, their time histories. With a more capable representation of the organizing parameters and the target electron energy flux observations, PrecipNet achieves a >50% reduction in errors from a current state‐of‐the‐art model oval variation, assessment, tracking, intensity, and online nowcasting (OVATION Prime), better captures the dynamic changes of the auroral flux, and provides evidence that it can capably reconstruct mesoscale phenomena. We create and apply a new framework for space weather model evaluation that culminates previous guidance from across the solar‐terrestrial research community.

-higgs-boson-event-detection icon -higgs-boson-event-detection

The Higgs boson is the fundamental particle associated with the Higgs field, a field that gives mass to other fundamental particles such as electrons and quarks. A particle’s mass determines how much it resists changing its speed or position when it encounters a force. Not all fundamental particles have mass. The photon, which is the particle of light and carries the electromagnetic force, has no mass at all.

customer_spent_at_clubmahindra_resort icon customer_spent_at_clubmahindra_resort

Club Mahindra in association with Analytics Vidhya organised the DataOlympics . The task is to use information that was available to construct a machine learning model that predicts the spending in response to the offer. Predict average spend on Food & Beverages by a Club Mahindra member. The model will be evaluated on the MSE/RMSE of your predictions on a test set.

patient-survival-prediction icon patient-survival-prediction

Developing patient survival prediction model is important in clinical research. As different levels of data may all contribute to patients’ survival, the prediction model using multiple omics data could achieve better performance.

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