Build your neural network easy and fast, 莫烦Python中文教学
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Updated
Mar 23, 2023 - Jupyter Notebook
Build your neural network easy and fast, 莫烦Python中文教学
Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学
🔬 Nano size Theano LSTM module
MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.
Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.
Educational deep learning library in plain Numpy.
My workshop on machine learning using python language to implement different algorithms
Artificial Intelligence Learning Notes.
Complementary code for the Targeted Dropout paper
Building a HTTP-accessed convolutional neural network model using TensorFlow NN (tf.nn), CIFAR10 dataset, Python and Flask.
Google Street View House Number(SVHN) Dataset, and classifying them through CNN
Dropout as Regularization and Bayesian Approximation
Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.
Bayesian Neural Network in PyTorch
TensorFlow in Practice Specialization. Join our Deep Learning Adventures community 🎉 and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time…
My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition
[TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
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