class Rishika:
def __init__(self):
self.name = "Rishika Nigam"
self.role = "AI/ML Developer & Data Scientist"
self.interests = ["Deep Learning", "NLP", "Remote Sensing", "Computer Vision"]
self.tools = ["Python", "TensorFlow", "PyTorch", "Scikit-learn", "Pandas"]
self.currently = "Exploring multimodal AI & satellite imagery analysis"
self.fun_fact = "I taught a model to read crops from space 🛰️"
def say_hi(self):
print("Thanks for visiting! Let's build something impactful together.")
me = Rishika()
me.say_hi()|
Fusing Sentinel-1 SAR and Sentinel-2 optical satellite data for precision crop classification using advanced ML/DL models.
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End-to-end NLP pipeline to classify Amazon reviews as positive, negative, or neutral — from raw text to actionable insights.
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Languages & Frameworks
Data & Visualization
Tools
- 🛰️ Advancing satellite-based crop monitoring with multimodal fusion techniques
- 🤖 Exploring LLMs for domain-specific text classification
- 📚 Learning MLOps to bring models from notebooks to production
Open to research collaborations, ML projects, and interesting conversations!