Introduction to Neural Networks
Course
558 Learners Already enrolled- Understand the core concepts behind neural networks and their structure.
- Grasp the role and functionality of a single neuron and perceptron layers in artificial intelligence.
- Comprehend activation functions, along with forward and backward propagation techniques.
- Explore applications of deep learning in real-world scenarios.
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There are 3 modules in this course
Neural networks are powerful algorithms inspired by the structure of the human brain that are used to solve complex machine learning problems. You will build your own Neural Network from scratch to understand how it works. After this course, you will be able to create neural networks for solving classification and regression problems using the scikit-learn library.- Single Neuron ImplementationPreview
- Challenge: Creating a NeuronPreview
- Perceptron LayersPreview
- Challenge: Creating a PerceptronPreview
- Forward PropagationPreview
- Loss FunctionPreview
- Backward PropagationPreview
- Backpropagation ImplementationPreview
- Model TrainingPreview
- Challenge: Training the PerceptronPreview
- Model EvaluationPreview
- Challenge: Evaluating the PerceptronPreview
- Neural Network with scikit-learnPreview
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Showing 3 of 17 reviews
Athanasios Samaras
4
Reviewed on Feb 12, 2025
Good hints provided, nice skeleton code
Feri
5
Reviewed on Dec 16, 2024
Create from scratch was a good experience and helps a lot in understanding. Good idea!
Clyde Abder
3
Reviewed on Oct 24, 2024
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