Harsh Patel is an A.I. developer and computer science graduate student with experience in machine learning, automation, computer vision, and data science. He has worked on AI projects involving sequential models, ETL, da…
Harsh Patel is an A.I. developer and computer science graduate student with experience in machine learning, automation, computer vision, and data science. He has worked on AI projects involving sequential models, ETL, dashboards, and automation scripts, and has experience with Python, JavaScript, Node.js, Docker, AWS, Azure, and related ML/MLOps tools.
• Spearheaded a Proof of Concept, implementing sequential models like RNN and LSTM for precise WAN alarm predictions on a 10-million-row time series dataset, achieving impactful results.
• Leading a pivotal AI project in early-stage data analysis, focused on anticipating outages. In the data collection phase, utilizing ETL processes to seamlessly integrate diverse log data into a centralized ELK-powered data lake. Innovated Power BI dashboards with Python and Linux utilities, monitoring DNS server QPS and efficiently ingesting results into Azure table storage
Spearheaded a Proof of Concept, implementing sequential models like RNN and LSTM for precise WAN alarm predictions on a 10-million-row time series dataset, achieving impactful results.
Leading a pivotal AI project in early-stage data analysis, focused on anticipating outages.
Utilized ETL processes to seamlessly integrate diverse log data into a centralized ELK-powered data lake.
Innovated Power BI dashboards with Python and Linux utilities.
Monitored DNS server QPS.
Efficiently ingested results into Azure table storage.
Engineered Python and JavaScript automation scripts.
Leveraged Git extensively to significantly enhance testing efficiency with TestComplete/Selenium.
Optimized critical processes.
Analyzed project requirements.
Tracked quality metrics in Azure DevOps for a robust SDLC.
Operated server-side and API scripts in Node.js.
Developed a Python automation script for data retrieval from Oracle and NoSQL(MongoDB).
Generated a final CSV file.
Gained familiarity with technologies including Kafka, Postman, ElasticSearch, Ruby and Docker.
Formulated and implemented machine learning algorithms with a 95% success rate.
Crafted impactful dashboards with a 100% satisfaction rate among stakeholders.
Achieved a remarkable 98% accuracy in image recognition utilizing YOLO and Inception models.
Delivered a notable project.
The AI-first Recruitment Operating System that unifies and automates the entire hiring lifecycle for modern enterprises worldwide.
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