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Mastering Feed Ranking Models with Machine Learning

Prem Vishnoi(cloudvala)
NextGenAI
Published in
6 min readNov 30, 2024

Learn about the Feed Ranking system architecture and the model requirements

We will cover the following topic

Model Engg

  • Feature engineering
  • Training data

Model

  • Selection
  • Evaluation

ML Feed Ranking Model Overview

The ML Feed Ranking Model personalizes user feeds (e.g., LinkedIn feed) to maximize engagement (e.g., Click-Through Rate, CTR). The model ranks content based on user preferences and interactions, incorporating features, data, and algorithms

1.Feature engineering

Feature engineering involves creating features to represent user behavior, activity, and relationships effectively.

Feature extraction in Python:

import pandas as pd
from sklearn.preprocessing import OneHotEncoder
from

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NextGenAI
NextGenAI

Published in NextGenAI

Explore the future of AI with tutorials, insights, and projects in Generative AI, Large Language Models, and beyond. From mastering PyTorch and TensorFlow to creating groundbreaking applications, we simplify complex concepts fo

Prem Vishnoi(cloudvala)
Prem Vishnoi(cloudvala)

Written by Prem Vishnoi(cloudvala)

Head of Data and ML experienced in designing, implementing, and managing large-scale data infrastructure. Skilled in ETL, data modeling, and cloud computing

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