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通过阅读网上的资料代码，进行自我加工，努力实现常用的机器学习算法。实现算法有KNN、Kmeans、EM、Perceptron、决策树、逻辑回归、svm、adaboost、朴素贝叶斯

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a-stock-prediction-algorithm-based-on-machine-learning

（陆续更新）重新整理过的基于机器学习的股票价格预测算法，里面包含了基本的回测系统以及各种不同的机器学习算法的股票价格预测，包含：LSTM算法、Prophet算法、AutoARIMA、朴素贝叶斯、SVM、随机森林等

anomaly-detection-hierarchical-deep-learning-model

Deep learning meta-model for water consumption analysis. Recognizes patterns, detects anomalies, classifies behavior, and visualizes data via web app leveraging LSTMs & Transformers and achieving high accuracy in consumption prediction.

attention-clx-stock-prediction

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction

captcha_trainer

[验证码识别-训练] This project is based on CNN/ResNet/DenseNet+GRU/LSTM+CTC/CrossEntropy to realize verification code identification. This project is only for training the model.

cs330-deep-multi-task-meta-learning

CS330 Deep Multi Task and Meta Learning Assignment. Stanford University

cuda_python

CUDA Python 科普之夜 | 手把手教你写GPU加速代码

demo_marchenko_pastur_analysis

Presentation held at IMR Machine Learning journal club 15. October 2020. Demo Marcenko Pasture distribution applied to eigenvalues of random matrix

du_crawler

作者想用纯golang（不用任何爬虫框架）写一个爬虫，以体现golang语言作为网络语言的优点。 共分为5个目录。每个目录是彼此分开，各不影响的。 可以一步一步看到一个代码整体的演化过程，其实很容易就可以发现并没有改动多少代码，就可以从一个单任务版本的代码演化成一个并发版本的爬虫了，接着由并 发版本的会演化成分布式版本的爬虫了。

dva

Code release for "Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction" https://arxiv.org/abs/2309.00073

hands-on-meta-learning-with-python

Hands-On Meta Learning with Python

hands-on-meta-learning-with-python01

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

hemocyte

hub-recsys

A python library contain classic algorithms and deep models on recommender system

imageprocessing-experiments

Noise removal, Image enhancement, Computer Vision application of PCA

lstm_pytorch_electric-load-forecasting

使用PYTorch框架建立的一个简单的LSTM模型来进行电力负荷预测

marchenko-pastur-pca

Tutorial and code for principal components analysis with Marchenko-Pastur Law-based denoising algorithm.

matlabbookanswer

Matlab程序设计与应用（第3版，刘卫国著）课后习题与实验-参考答案

medicalgpt

MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. 训练医疗大模型，实现了包括增量预训练、有监督微调、RLHF(奖励建模、强化学习训练)和DPO(直接偏好优化)。

meta-heuristic-based-timeseries

Crude oil price forecasting: a meta-heuristic optimisation framework to optimize the hyperparameters of various deep learning architectures, including LSTM, CNN-LSTM, CNN-LSTM-attention, GRU, and encoder-decoder-LSTM, for multi-step crude oil price forecasting.

meta-learning-lstm-pytorch

pytorch implementation of Optimization as a Model for Few-shot Learning

mp-pca-denoising

Matlab implementation of Marchenko Pastur denoising (Veraart et al, NeuroImage 142 (2016) 394–406)

mt_bigru_attention_keras

multi_task-learning

多任务学习MMOE和PLE

noise-removal-techniques-in-ultrasound-images

Implement RPCA, PCA, Median filter and Fuzzy image filter methods

pca-lda-fda

This repository contains python implementation of PCA, LDA and FDA from scratch. Noise removal effect of PCA is also visualized.

reptile-pytorch

PyTorch implementation of code for the paper "On First-Order Meta-Learning Algorithms"

seq2seq

Sequence to Sequence Learning with Keras

seq2seq-keras

这是一个利用keras实现seq2seq模型的仓库，大家可以通过这个仓库学习到许多的seq2seq的例子