https://speech.ee.ntu.edu.tw/~hylee/ml/2021-spring.php Mendeley https://www.mendeley.com/ Google - Welcome to Colab https://colab.research.google.com/# Overview of Colaboratory Features https://colab.research.google.com/notebooks/basic_features_overview.ipynb Charting in Colaboratory https://colab.research.google.com/notebooks/charts.ipynb Importing a library that is not in Colaboratory https://colab.research.google.com/notebooks/snippets/importing_libraries.ipynb Forms https://colab.research.google.com/notebooks/forms.ipynb Google - Introduction to Machine Learning https://developers.google.com/machine-learning/intro-to-ml Google - ML Practicum: Image Classification https://developers.google.com/machine-learning/practica/image-classification CS231n Convolutional Neural Networks for Visual Recognition https://cs231n.github.io/ GeeksforGeeks - Introduction to Convolution Neural Network https://www.geeksforgeeks.org/introduction-convolution-neural-network/ [w/ notes] Backpropagation https://www.geeksforgeeks.org/backpropagation-in-data-mining/ [w/ notes] Activation Functions https://www.geeksforgeeks.org/activation-functions-neural-networks/ [w/ notes] Intro. to CNN Pooling Layer https://www.geeksforgeeks.org/cnn-introduction-to-pooling-layer/ [w/ notes] NN Beginners Guide https://www.geeksforgeeks.org/neural-networks-a-beginners-guide/ [w/ notes] Generalization in Neural Networks Key words: generalisation, overfitting, balance, dropout, ensemble, regularisation https://www.kdnuggets.com/2019/11/generalization-neural-networks.html [w/ notes] Neural Architecture Search: Everything You Need to Know https://deci.ai/neural-architecture-search/ [w/ notes] AutoML https://www.automl.org/automl/ [w/ notes] Neural architecture search https://en.wikipedia.org/wiki/Neural_architecture_search EfficientNet: Improving Accuracy and Efficiency through AutoML and Model Scaling https://blog.research.google/2019/05/efficientnet-improving-accuracy-and.html?ref=blog.streamlit.io&m=1 Wikipedia - Genetic algorithm https://en.wikipedia.org/wiki/Genetic_algorithm Wikipedia - Genetic representation https://en.wikipedia.org/wiki/Genetic_representation MathWorks - Genetic Algorithm https://www.mathworks.com/help/gads/genetic-algorithm.html GeeksforGeeks - Genetic Algorithms https://www.geeksforgeeks.org/genetic-algorithms GeeksforGeeks - Encoding Methods in Genetic Algorithm https://www.geeksforgeeks.org/encoding-methods-in-genetic-algorithm Introduction to Genetic Algorithms https://courses.cs.washington.edu/courses/cse473/06sp/GeneticAlgDemo The CIFAR-10 dataset https://www.cs.toronto.edu/~kriz/cifar.html Papers with Code - Image Classification on CIFAR-10 https://paperswithcode.com/sota/image-classification-on-cifar-10 https://paperswithcode.com/paper/threshnet-an-efficient-densenet-using https://paperswithcode.com/paper/densely-connected-convolutional-networks GitHub - liuzhuang13/DenseNet: Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award). https://github.com/liuzhuang13/DenseNet https://www.geeksforgeeks.org/implementing-ann-training-process-in-python/ https://vitalflux.com/different-types-of-cnn-architectures-explained-examples/ https://www.jeremyjordan.me/convnet-architectures/ https://towardsdatascience.com/a-guide-to-an-efficient-way-to-build-neural-network-architectures-part-i-hyper-parameter-8129009f131b https://towardsdatascience.com/a-guide-to-an-efficient-way-to-build-neural-network-architectures-part-ii-hyper-parameter-42efca01e5d7 https://www.sciencedirect.com/science/article/abs/pii/S2210650222001547 https://www.kdnuggets.com/2017/01/current-state-automated-machine-learning.html https://playground.tensorflow.org/ Seen pages: https://bair.berkeley.edu/blog/2021/10/25/eigenlearning/ np-complete https://www.britannica.com/science/NP-complete-problem perceptron https://en.wikipedia.org/wiki/Perceptron MLP https://en.wikipedia.org/wiki/Multilayer_perceptron fnn https://en.wikipedia.org/wiki/Feedforward_neural_network act func https://en.wikipedia.org/wiki/Activation_function