13 practical features you must know about PyTorch

1. DatasetFolder When learning PyTorch, one of the first things people need to do is to implement some kind of Dataset. This is a low-level mistake. There is no need to waste time writing such things. Typically, a Dataset is either a data list (or a numpy array) or a file on disk. Therefore, organizing data on disk is better than writing a cus ...

Added by fitzbean on Thu, 10 Mar 2022 15:33:35 +0200

Reinforcement learning algorithm: PPO2 creates a bitcoin trading robot that won't lose money

Creating a bitcoin trading robot will not lose money In this article, we will create a deep reinforcement learning agent to learn to make money through bitcoin trading. In this tutorial, we will use the PPO agent in OpenAIgym and the stable baselines Library (a branch of OpenAI's baselines Library). The purpose of this series of articles is to ...

Added by decessus on Mon, 07 Mar 2022 21:53:14 +0200

Datawhale zero foundation entry data mining - Task3 Feature Engineering

Datawhale zero foundation entry data mining - Task3 Feature Engineering 3, Characteristic engineering objectives Game Title: Zero basic entry data mining - used car transaction price prediction 3.1 characteristic engineering objectives Further analyze the characteristics and process the data Complete the analysis of characteristic enginee ...

Added by noiseusse on Sat, 05 Mar 2022 02:57:32 +0200

Principal component analysis and its application in face recognition

Recently, I was studying Turing textbook by myself< Python Basic course of machine learning ", take some notes in the form of blog on csdn. We may have many purposes in using unsupervised learning for data transformation. The most common purpose is to visualize, compress data, and find a more informative data representation for further ...

Added by jateeq on Thu, 03 Mar 2022 13:47:38 +0200

Data mining project -- prediction of accommodation reservation results for new Airbnb users

abstract Based on the prediction of the accommodation reservation results of new Airbnb users, this paper completely describes the whole process from data exploration to feature engineering to model construction. Project address: Airbnb New User Bookings | Kaggle Of which: 1. The data exploration part is mainly based on pandas library, using t ...

Added by TheBrandon on Wed, 02 Mar 2022 16:27:52 +0200

Teach you: personal credit default prediction model

Series articles Chapter VIII Teach you hand in hand: Stock Forecasting System Based on LSTMChapter VII Teach you by hand: fruit classification and recognition system based on depth residual network (ResNet)Chapter VI Hand in hand teach you: face recognition video coding 1, Project introduction This paper mainly introduces how to us ...

Added by rish1103 on Wed, 02 Mar 2022 06:10:45 +0200

Machine learning notes - introductory case 4 of exploratory data analysis (EDA)

1, Data set description 1. Data set Tabular Playground Series - Feb 2022 | KagglePractice your ML skills on this approachable dataset!https://www.kaggle.com/c/tabular-playground-series-feb-2022/data For this challenge, you will predict bacterial species based on repeated lossy measurements of DNA fragments. The fragment with length of 10 is ...

Added by Gregadeath on Tue, 01 Mar 2022 06:46:03 +0200

Crawling through the list of Google Scholar papers, how to use public data for co-author analysis?

  Preface Before, my classmates selected tutors for postgraduate study. I helped them refer to them. I found that some teachers are very young, but the data of Google Scholar are ridiculously high (mainly citation and h-index), and even easily crush some calf guides in the ears of the population. Intuitively, this kind of data should be fal ...

Added by Goon on Tue, 01 Mar 2022 06:07:14 +0200

R language ARMA-GARCH-COPULA model and financial time series case

Original link: http://tecdat.cn/?p=3385Original source: Tuo end data tribal official accountRecently, I was asked to write a copulas survey on financial time series. Obtain the description of various models from the read data, including some graphics and statistical output.> oil = read.xlsx(temp,sheetName ="DATA",dec =",")Then we can draw ...

Added by T_Hayden on Mon, 28 Feb 2022 11:09:42 +0200

Kaggle Titanic

Kaggle Titanic (1) Question: On April 15, 1912, the Titanic sank, and everyone on board did not have enough lifeboats, resulting in the death of 1502 of the 2224 passengers and crew. Although there are some luck factors in surviving, it seems that some people are more likely to survive than others. Build a prediction model to answer the quest ...

Added by lesmith on Sat, 26 Feb 2022 12:22:42 +0200