Ratan Gupta

AI Researcher

Ghaziabad, Uttar Pradesh, India8 yrs 2 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in Machine Learning and Deep Learning applications
Proven track record in AgriTech innovations
Strong background in full-stack development

Stackforce AI infers this person is a Data Scientist specializing in AgriTech and Machine Learning.

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Skills

Core Skills

Machine LearningDeep LearningFull-stack DevelopmentSoftware Development

Other Skills

Artificial IntelligenceVideo AnalyticsPythonopenCVscikit-learnKerasGoogle Earth EngineGIS (GDAL/OGR)GPUImage RecognitionAngularPHPSQLMongoDBElastic Search

Experience

8 yrs 2 mos

Total Experience

1 yr 9 mos

Average Tenure

2 yrs 1 mo

Current Experience

Confidential

Lead Data Scientist

Apr 2024 – Present · 2 yrs 1 mo · On-site

Artificial Intelligence, Video Analytics

Artificial IntelligenceVideo AnalyticsMachine LearningDeep Learning

Absolute®

2 roles

Senior Data Scientist

Mar 2021 – Jun 2023 · 2 yrs 3 mos

Lead Data Scientist

Feb 2021 – Jun 2024 · 3 yrs 4 mos

Agribazaar.com

2 roles

Machine Learning | Deep Learning | Computer Vision | Data Scientist

Feb 2019 – Feb 2021 · 2 yrs · Noida Area, India

Working on Crop Classification based on satellite image Sentinel-2 using machine learning: Trying to build Crop classification algorithm (i.e collection of no. of ML algorithms ) that will classify number of category and mask category in whole TILE image category wise .
Tools & Libraries used: Python, openCV, scikit-learn, Keras, Google Earth Engine, GIS (GDAL/OGR), GPU
Created Weather based Yield prediction model for crops district wise using machine learning statistical techniques.
Working on satellite image based yield prediction model.
Worked on commodity quality prediction using deep learning research based algorithms.
Worked on Deep Learning Research Based Algorithms for predict commodity qualities Using Image Recognition (semantic & label recognition) & research-based algorithm (framework Keras & tensorflow)
Crop Identification:
Methodology Used: Python, R, Scikit-learn, Time series, Opencv, GIS (GDAL/OGR), Database (SQL), Image Source (Sentinel-1 & Sentinel-2 satellite data)