Helps in knowing intention of customers by using categorisation and using LSTM based models for retention of memory.

describe what can people use it for, or how it makes existing tasks easier/safer e.t.c (markdown supported)

The problem it solves

tell us about any specific bug or hurdle you ran into while building this project. how did you get over it? (markdown supported)

Challenges we ran into

Winter of Code 4.0

TensorFlow

scikit-learn

NumPy

pandas

Matplotlib

Python

Proposal for DL Simplified by Soumya Sourav

I see my idea fitting well with Aptos because its high-throughput and reliable Layer 1 blockchain can handle the large-scale data processing needed for tracking user intentions and categorizing products. Using the Move programming language for secure and flexible smart contracts, I could implement the logic for recommendations and product classifications effectively. By building on Aptos, I can ensure data integrity, scalability, and security, while also enabling a decentralized and transparent approach to user insights and product management.

Aptos

Celestial

Proposal for DL Simplified by Soumya Sourav

Proposal: DL simplified: Online Shoppers Intention Prediction

Proposal for DL Simplified by Soumya Sourav

Proposal: DL simplified: Online Shoppers Intention Prediction

The problem Proposal for DL Simplified by Soumya Sourav solves

Challenges I ran into

Aptos

Discussion

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