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Complete learning from scratch, machine learning and deep learning, including theory and code implementation, mainly using scikit and mxnet, and some practices (on kaggle)

2022-04-23 07:55:00 【Fish in Siyuan Lake】

Preface

As a pair of 2020.6 Review and summary of one month learning machine learning and in-depth learning
Complete learning from scratch, traditional machine learning and classical deep learning
It only needs python Basics , It's better to have a foundation in linear algebra , No, it's not a big problem

machine learning

Machine learning series （ One ） numpy Use
Machine learning series （ Two ） kNN（k Nearest neighbor algorithm ） use scikit
Machine learning series （ 3、 ... and ） Linear regression , use scikit
Machine learning series （ Four ） Gradient descent method
Machine learning series （ 5、 ... and ） PCA（ Principal component analysis ） use scikit
Machine learning series （ 6、 ... and ） use scikit distinguish MNIST Data sets , be used kNN and PCA
Machine learning series （ 7、 ... and ） Polynomial regression and model generalization （ The learning curve 、 Cross validation 、 Regularization ）
Machine learning series （ 8、 ... and ） Logistic regression and multi classification problems
Machine learning series （ Nine ） Evaluation of classification results （ Confusion matrix 、 accuracy 、 Recall rate 、F1、ROC）
Machine learning series （ Ten ） Support vector machine SVM
Machine learning series （ 11、 ... and ） Decision tree
Machine learning series （ Twelve ） Integrated learning

Deep learning

Deep learning series （ One ） Multilayer perceptron
Deep learning series （ Two ） Basic knowledge of convolutional neural network
Deep learning series （ 3、 ... and ） Deep convolution neural network （AlexNet、VGG、NiN、GoogleNet）
Deep learning series （ Four ） Batch normalization of deep convolution neural networks 、ResNet、DenseNet
Deep learning series （ 5、 ... and ） Cyclic neural network
Deep learning series （ 6、 ... and ） Cyclic neural network GRU、LSTM、 Two way circulation
Deep learning series （ 7、 ... and ） optimization algorithm （ gradient descent 、 Momentum method 、AdaGrad Algorithm 、RMSProp Algorithm 、AdaDelta Algorithm 、Adam Algorithm ）
Deep learning series （ 8、 ... and ） Computing performance （ Imperative programming and symbolic programming 、 Asynchronous computation 、 many GPU Calculation )
Deep learning series （ Nine ） Model generalization ability of computer vision （ Image widening and fine tuning ）
Deep learning series （ Ten ） Object detection in computer vision （object detection）

practice

kaggle Housing forecast Linear regression

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