Machine Learning
1,521 learners
Neural Networks Basics from Scratch
Dive deep into the theory and implementation of Neural Networks. This course will have you implementing tools at the heart of modern AI such as Perceptrons, activation functions, and the crucial components of multi-layer Neural Networks. All of this without the help of high-level libraries leaves you with a profound understanding of the underpinning mechanisms.
Python
3 lessons
10 practices
2 hours
Deep Learning and Neural Networks
Lessons and practices
Perceptron Logic Probe Decision-Making
Perceptron Prediction Calibration
Code the Perceptron's Decision Function
Step Function in Action
Comparing Function: Sigmoid and Tanh
Sigmoid Activation Function Implementation
Training a Neural Network to Solve XOR
Implement Prediction in the Neural Network
Implement Weight Update in Neural Network
Implement Sigmoid Derivative and Prediction Function in a Neural Network
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