Ritika Yogi

AI Researcher

Jaipur, Rajasthan, India0 mo experience
AI EnabledAI ML Practitioner

Key Highlights

  • Built end-to-end ML applications.
  • Expert in data preparation and model evaluation.
  • Strong collaboration and communication skills.
Stackforce AI infers this person is a Data Science and AI Engineer with a focus on real-time applications.

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Skills

Core Skills

Machine LearningOpencv

Other Skills

TensorFlowPythonNumPyPython (Programming Language)Artificial Intelligence (AI)Data AnalysisTableauSpreadsheetsData ModelingComputer GraphicsAutoCADMySQLWindowsLinuxOperating Systems

About

Data storyteller turned model builder I believe the best Al feels invisible to the user yet clear to the team. My journey started with spreadsheet reports and led to end-to-end ML apps such as: An Al doctor that processes symptoms and proposes likely conditions with scikit-learn A dashboard revealing worldwide Netflix habits, sliced by hour and genre A computer-vision gatekeeper tallying students in real time at campus events Each project deepened my grasp of data prep, feature design, model evaluation, RESTful APIs, and deployment using Flask/Streamlit. Tools I reach for daily: Python, Pandas, NumPy, scikit-learn, and basic OpenCV. I'm now extending my reach into cloud pipelines and MLOps, aiming for smoother releases and monitored models. Colleagues describe me as consistent, curious, and easy to pair-program with. I like small feedback loops, clear naming, and dashboards that explain what the model just did. I'm actively searching for an Al/ML or Machine Learning Engineer internship where I can keep building useful systems and pick up best practices from seasoned teams. If you're hiring-or just want to swap project stories-let's connect. Check out the medical diagnosis demo pinned on my profile and tell me what you think!

Experience

0 mo
Total Experience
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Average Tenure
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Current Experience

Techsaksham

AI Intern

Mar 2025Mar 2025 · 0 mo · Jaipur, Rajasthan, India · Remote

  • ◦ Built a Python-based real-time system to detect facial emotions and hand gestures using TensorFlow,
  • OpenCV, andMediaPipe
  • ◦ Implemented live video processing with accurate emotion classification and gesture tracking
  • ◦ Handled model integration, backend logic, and optimized performance for real-time inference
  • ◦ Used VS Code, GitHub, and pre-trained model files for development and version control
Machine LearningOpenCV

Education

JECRC University

Bachelor of Technology - BTech — COMPUTER AND INFORMATION SCIENCES AND SUPPORT SERVICES

Jan 2022May 2026

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