Lesson 2: Introduction to Neural Networks_II

Udacity: Intro to Deep Learning with PyTorch:Day 24 of #60daysofudacity - Logistic Regression:Take your dataPick a random modelCalculate the errorMinimize the error, and obtain a better model- Calculating the Error Function- Minimizing the error functionDay 25 of #60daysofudacity- Gradient CalculationIn order to minimize the error function, we need to take some derivatives. So let's compute the … Continue reading Lesson 2: Introduction to Neural Networks_II

Lesson 2: Introduction to Neural Networks_I

Udacity: Intro to Deep Learning with PyTorch: Day 21 of #60daysofudacity: Lesson 2: Introduction to Neural Networks - Why "Neural Networks"?- Perceptron Algorithm  - Error FunctionAn error function is simply something that tells us how far we are from the solution- Log-loss Error Function- Discrete vs Continuous PredictionsDay 22 of #60daysofudacity: - The Softmax Functionsoftmax function, which is the … Continue reading Lesson 2: Introduction to Neural Networks_I