qian-cloud's Stars
forthespada/InterviewGuide
🔥🔥「InterviewGuide」是阿秀从校园->职场多年计算机自学过程的记录以及学弟学妹们计算机校招&秋招经验总结文章的汇总，包括但不限于C/C++ 、Golang、JavaScript、Vue、操作系统、数据结构、计算机网络、MySQL、Redis等学习总结，坚持学习，持续成长！
entron/entity-embedding-rossmann
Mcompetitions/M4-methods
Data, Benchmarks, and methods submitted to the M4 forecasting competition
nlpjoe/Coding4Interviews
Leetcode、剑指Offer——名企面试官精讲典型编程题
Jenniferz28/Time-Series-ARIMA-XGBOOST-RNN
Time series forecasting for individual household power prediction: ARIMA, xgboost, RNN
todorex/Coding-Interviews
📚剑指Offer（java版）
imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict
Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets
haiyusun/coding-interviews
《剑指offer》（第二版）Java实现
cyoon1729/deep-Q-networks
Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51
LyricYang/Internet-Recruiting-Algorithm-Problems
《程序员代码面试指南》、公司招聘笔试题、《剑指Offer》、算法、数据结构
Diyago/ML-DL-scripts
The repository provides usefull python scripts for ML and data analysis
wepe/CaiNiao-DemandForecast-StoragePlaning
1st Place Season one & 6th Place Season two
hosseinshn/Basic-Multi-task-Learning
This is a repository for Multi-task learning with toy data in Pytorch and Tensorflow
bojone/ee-2019-baseline
面向金融领域的事件主体抽取（ccks2019），一个baseline
marsprince/SwordForOffer
剑指Offer java版
timothyyu/wsae-lstm
implementation of WSAE-LSTM model as defined by Bao, Yue, Rao (2017)
reddyprasade/Machine-Learning-with-Scikit-Learn-Python-3.x
In general, a learning problem considers a set of n samples of data and then tries to predict properties of unknown data. If each sample is more than a single number and, for instance, a multi-dimensional entry (aka multivariate data), it is said to have several attributes or features. Learning problems fall into a few categories: supervised learning, in which the data comes with additional attributes that we want to predict (Click here to go to the scikit-learn supervised learning page).This problem can be either: classification: samples belong to two or more classes and we want to learn from already labeled data how to predict the class of unlabeled data. An example of a classification problem would be handwritten digit recognition, in which the aim is to assign each input vector to one of a finite number of discrete categories. Another way to think of classification is as a discrete (as opposed to continuous) form of supervised learning where one has a limited number of categories and for each of the n samples provided, one is to try to label them with the correct category or class. regression: if the desired output consists of one or more continuous variables, then the task is called regression. An example of a regression problem would be the prediction of the length of a salmon as a function of its age and weight. unsupervised learning, in which the training data consists of a set of input vectors x without any corresponding target values. The goal in such problems may be to discover groups of similar examples within the data, where it is called clustering, or to determine the distribution of data within the input space, known as density estimation, or to project the data from a high-dimensional space down to two or three dimensions for the purpose of visualization (Click here to go to the Scikit-Learn unsupervised learning page).
aldente0630/mofc-demand-forecast
Time Series Forecasting for the M5 Competition
LiYouru0228/EA-LSTM
EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction
tankwin08/Bayesian_uncertainty_LSTM
Bayesian, Uncertainty, Neutral Networks, LSTM, time series
jessgess/Time_Series_Analysis_ARIMA
Time Series analysis with Python and ARIMA model to forecast Bitcoin price
MaximoDouglas/systemic-blood-pressure-regression
Regression with SVR, CNN and CNN-LSTM
predicthq/phq-data-science-docs
PredictHQ’s Data Science documentation
sdwww/diagnosis_prediction_study
基于注意力机制的疾病诊断预测模型
RuichongWang/LSTM-with-Continuous-Wavelet-Transformation-in-Time-Series-Prediction
khaykingleb/stock-price-forecasting
GA-optimized RNNs for enhanced stock price forecasting
pzczxs/MTLSSVM
Multi-Task Least-Squares Support Vector Machines
maziars/Binary_SVM_MTL
wzy6642/ICBDC-2019
The Stock Classification Based on Entropy Weight Method and Improved Fuzzy C-means Algorithm
ZhuJD-China/DeepLearning
DeepLearning papers