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Python Academy · Lesson

Introduction to Neural Networks

Explore the fundamentals of neural networks and how they work.

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Introduction to Neural Networks

Neural networks are a subset of machine learning algorithms inspired by the structure and functioning of the human brain. They are powerful tools for tasks like image recognition, natural language processing, and more.

In this lesson, you’ll learn the fundamentals of neural networks and how they work.

Introduction to Neural Networks — illustration 1

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What is a Neural Network?

A neural network is composed of layers of interconnected nodes (neurons). Each neuron processes input data and passes it to the next layer. Key components include:

  • Input Layer: Receives input data.
  • Hidden Layers: Perform computations on the data.
  • Output Layer: Produces the final result.

All lessons in this course

  1. Introduction to Machine Learning
  2. Supervised Learning with Scikit-Learn
  3. Unsupervised Learning
  4. Feature Engineering and Selection
  5. Introduction to Neural Networks
  6. Introduction to TensorFlow and Keras
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