Project introduction: "Machine Learning Deep Learning" practical training camp has started_bilibili_bilibili
"Machine Learning Deep Learning" practical training camp has started
Teaching content: machine learning, deep learning, text classification, computer vision, time series prediction
Course Catalog:
Regression task: Prediction of pollutant PM2.5 based on machine learning atmospheric data
Classification task: Predicting company qualifications based on machine learning
Time series weather prediction-xgboost grid parameter adjustment practice
Machine learning algorithms: ["knn", "svm", "RandomForest", "AdaBoost", "xgboost", "GradientBoosting", "LGBM"]
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Text classification-word2vec+svm+xgboost text sentiment analysis practice
bert_wwm Weibo text classification flask text classification system
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Vehicle recognition classification based on vgg network
Blurry image detection based on pytorch cnn ResNets convolutional network
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Pytoch framework builds lstm traffic passenger flow prediction
Pytorch builds transformer to predict iceberg trajectory
Pytoch framework builds lstm+transformer oil well data prediction
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Pytoch framework construction: time series prediction-time series convolution network TCN stock closing price opening price prediction prediction
Keras framework construction: high and low temperature weather prediction based on lstm+dnn network
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Graduation project python Opencv license plate recognition tracking and positioning system