Activation Functions Explained: Why ReLU Replaced Sigmoid

📰 Medium · Deep Learning

Learn why ReLU replaced Sigmoid as the primary activation function in neural networks and how to apply this knowledge to build better models

intermediate Published 13 Apr 2026

Action Steps

Explore the properties of Sigmoid and ReLU activation functions using Python libraries like TensorFlow or PyTorch
Compare the performance of models using Sigmoid and ReLU on a benchmark dataset
Implement ReLU in a neural network architecture to observe its effect on model training and accuracy
Analyze the impact of ReLU on model interpretability and feature learning
Experiment with other activation functions like Leaky ReLU or Swish to find the best fit for a specific problem

Who Needs to Know This

Data scientists and machine learning engineers can benefit from understanding the differences between activation functions to improve model performance and avoid common pitfalls

Key Insight

💡 ReLU is preferred over Sigmoid due to its ability to avoid vanishing gradients and promote sparse representations, leading to faster training and improved model performance

Key Takeaways

Learn why ReLU replaced Sigmoid as the primary activation function in neural networks and how to apply this knowledge to build better models

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Title: Activation Functions Explained: Why ReLU Replaced Sigmoid

URL Source: https://medium.com/@adityaa9971/activation-functions-explained-why-relu-replaced-sigmoid-26242bacdb6b?source=rss------deep_learning-5

Published Time: 2026-04-13T03:16:19Z

Markdown Content:
# Activation Functions Explained: Why ReLU Replaced Sigmoid | by ADITYA RANJAN | Apr, 2026 | Medium

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# Activation Functions Explained: Why ReLU Replaced Sigmoid

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The function inside every neuron that makes neural networks actually work and why choosing the wrong one breaks everything.

### about me

Aditya Ranjan

3rd-year ECE student at GGSIPU, Delhi. Self-learning Gen AI and full-stack development, and writing everything down so beginners don’t have to struggle the way I did. This is Blog #5 of the Gen AI Journey series if you missed Blog #4 on Neural Networks, read that first.

## Introduction

In Blog #4, we learned that every neuron compute

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Activation Functions Explained: Why ReLU Replaced Sigmoid

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