[Keras] Build a CNN model to classify Cifar-10
Cifar-10 is dataset like "MNIST", it have 60000 pictures, 10 types. One of types have 6000 pictures. 50000 training data and 10000 test data.
Read More »[Keras] Build a CNN model to classify Cifar-10Cifar-10 is dataset like "MNIST", it have 60000 pictures, 10 types. One of types have 6000 pictures. 50000 training data and 10000 test data.
Read More »[Keras] Build a CNN model to classify Cifar-10Softmax function, mapping the vector between (0, 1), also represents the probability distribution of each element (classification class) in the vector.
Read More »[Machine Learning] Introduction of Softmax functionRectified Linear Unit (ReLU), is a famous activation function in neural network layer, it is believed to have sine degree if biological principle, although I don't know what it is. =)
Read More »[Machine Learning] Introduction of ReLUSigmoid() function is a mapping function, it will map any variable (In the following content we write the the symbol x) to [0, 1]. And it is often used to be a activation function in neural network layer of Machine Learning.
Read More »[Machine Learning] Sigmoid function introductionGoogle Colab, its full name is "Google colaboratory", as the name suggests, it's a service provided by Google. The advantage of Colab is that it provides a free GPU. Although you can only use the time limit of 12 hours a day, and the model training too long will be considered to be dig in the cryptocurrency.
Read More »How to use the free GPU from Google ColabMnist is a classical database of handwritten digits. The number in it have [0-9]. Today I will note how to use Keras to build a CNN classifier to classify numbers.
Read More »[Keras] Use CNN to build a simple classifier to MNISTI will introduce PyTorch which is a very famous Machine Learning package, and note my experience of my study.
If I have no note, I'll forget these hahaha.
Read More »[PyTorch] Tutorial(1) What is Tensor?Scikit-Learn is a open source machine learning framework in Python. It has six domains:
Read More »[Scikit-Learn] Tutorial (0) What is "Scikit-Learn"