udacity kaggle

Udacity Android Learning Note: Lesson 4 Part A/titer1/archimedes of dry Goods shop choresSource: Https://code.csdn.net/titer1Contact: 13,073,161,968Disclaimer: This document is licensed under the following protocols: Free reprint-Non-commercial-non-derivative-retention Attribution | Creative Commons by-nc-nd 3.0, reproduced please specify the author and source.Tips:https://code.csdn.net/titer1/pat_aha/blob/master/markdown/android/SQL lesson4a-15课开始，之前

Udacity-android Study Notes: lesson 2, udacityandroidUdacity android lesson 2 Study Notes Prepared by: Taobao stores/titer1/ArchimedesSource: https://code.csdn.net/titer1Contact: September 1307316Statement: This article uses the following agreement for authorization: Free Reprint-non commercial-Non derivative-keep the signature | Creative Commons BY-NC-ND 3.0, reprint please indicate the author and the source.Tips: https://code.csdn.net/titer1/pat_aha

Udacity Android Learning Note: Lesson 4 Part B/titer1/archimedes of dry Goods shop choresSource: Https://code.csdn.net/titer1Contact: 13,073,161,968Disclaimer: This document is licensed under the following agreement: Free reprint-Non-commercial-non-derivative-retention Attribution | Creative Commons by-nc-nd 3.0, reproduced please specify the author and source.Tips:https://code.csdn.net/titer1/pat_aha/blob/master/markdown/android/4b，后期将拆分为4大小节强烈建议保留自己

Udacity Android Practice Note: Lesson 4 Part A/titer1/archimedes of dry Goods shop choresSource: Https://code.csdn.net/titer1Contact: 13,073,161,968 (SMS Best)Disclaimer: This document is licensed under the following protocols: Free reprint-Non-commercial-non-derivative-retention Attribution | Creative Commons by-nc-nd 3.0, reproduced please specify the author and source.Tips:https://code.csdn.net/titer1/pat_aha/blob/master/markdown/android/PrefaceThi

Udacity Android Practice Note: Lesson 4 Part B/titer1/archimedes of dry Goods shop choresSource: Https://code.csdn.net/titer1Contact: 13,073,161,968 (SMS Best)Disclaimer: This document is licensed under the following protocols: Free reprint-Non-commercial-non-derivative-retention Attribution | Creative Commons by-nc-nd 3.0. Reprint please indicate the author and source.Tips:https://code.csdn.net/titer1/pat_aha/blob/master/markdown/android/Summary

1. Why add pooling (pooling) to the convolutional networkIf you only use convolutional operations to reduce the size of the feature map, you will lose a lot of information. So think of a way to reduce the volume of stride, leaving most of the information, through pooling to reduce the size of feature map.Advantages of pooling:1. Pooled operation does not increase parameters2. Experimental results show that the model with pooling is more accurateDisadvantages of pooling:1. Because the stride of t

Udacity android Practice Notes: lesson 4 part B, udacityandroidUdacity android Practice Notes: lesson 4 part B Prepared by: Taobao stores/titer1/ArchimedesSource: https://code.csdn.net/titer1Contact: September 1307316 (best SMS)Statement: This article uses the following agreement for authorization: Free Reprint-non commercial-Non derivative-keep the signature | Creative Commons BY-NC-ND 3.0, reprint please indicate the author and the source.Tips: http

Udacity android Practice Notes: lesson 4 part a, udacityandroidUdacity android Practice Notes: lesson 4 part Prepared by: Taobao stores/titer1/ArchimedesSource: https://code.csdn.net/titer1Contact: September 1307316 (best SMS)Statement: This article uses the following agreement for authorization: Free Reprint-non commercial-Non derivative-keep the signature | Creative Commons BY-NC-ND 3.0, reprint please indicate the author and the source.Tips: https:

Get started with Kaggle -- use scikit-learn to solve DigitRecognition and scikitlearnGet started with Kaggle -- use scikit-learn to solve DigitRecognition Problems @ Author: wepon @ Blog: http://blog.csdn.net/u012162613 1. Introduction to scikit-learn Scikit-learn is an open-source machine learning toolkit based on NumPy, SciPy, and Matplotlib. It is written in Python and covers classification, Regression

Big Data Competition Platform--kaggle Introductory articleThis article is suitable for those who just contact Kaggle, want to become familiar with Kaggle and finish a contest project independently, for the Netizen who has already competed on the Kaggle, can not spend time reading this article. This article is divided i

"Python Machine learning and practice – from scratch to the road to Kaggle race" very basicThe main introduction of Scikit-learn, incidentally introduced pandas, NumPy, Matplotlib, scipy.The code of this book is based on python2.x. But most can adapt to python3.5.x by modifying print ().The provided code uses Jupyter Notebook by default, and it is recommended to install ANACONDA3.The best is to https://www.kaggle.com registered account, run the fourth

matplotlib.pyplot as Plt %matplot Lib inline trainpath = str (' e:\\kaggle\invasive_species\\train\\ ') testpath = str (' E:\\kaggle\\invasive_ Species\\test\\ ') n_tr = Len (Os.listdir (trainpath)) print (' num of training files: ', n_tr) Num of training files:2295 You can see the specifics of the train_labels.csv, which is shown in the table below, where the data is already scrambled, and the samples l

Kaggle Big Data Contest Platform IntroductionBig Data Competition platform, domestic is mainly Tianchi Big Data competition and datacastle, foreign main is kaggle.kaggle is a data mining competition platform, The website is: https://www.kaggle.com/. A lot of institutions, enterprises will issue, description, expectations posted on the Kaggle, in a competitive way to the vast number of data scientists to col

Getting started with Kaggle-using Scikit-learn to solve digitrecognition problems@author: Wepon@blog: http://blog.csdn.net/u0121626131, Scikit-learn simple introductionScikit-learn is an open-source machine learning toolkit based on NumPy, SciPy, and Matplotlib. Written in the Python language. Mainly covers classification,back and clustering algorithms such as KNN, SVM, logistic regression, Naive Bayes, random forest, K-means and many other algorithms

training data contains a list of label and 784 column pixel values. The test data does not have a label column. Objective: To train the training data, to obtain the model and predict the label value of the test data.The following restores the picture from the pixel value to the actual picture, using Ipython notebook:In [1]:PwdC:\Users\zhaohf\DesktopIn [5]:CD .. / .. / .. / Workspace / Kaggle / Digitrecognizer / Data /C:\workspace\

Kaggle Data Mining -- Take Titanic as an example to introduce the general steps of data processing, kaggletitanic Titanic is a just for fun question on kaggle, there is no bonus, but the data is neat, it is best to practice it. This article uses Titanic data and uses a simple decision tree to introduce the general process and steps of data processing. Note: The purpose of this article is to help you get st

Titanic is a kaggle on the just for fun, no bonuses, but the data neat, practiced hand best to bring.Based on Titanic data, this paper uses a simple decision tree to introduce the process and procedure of processing data.Note that the purpose of this article is to help you get started with data mining, to be familiar with data steps, processesDecision tree model is a simple and easy-to-use non-parametric classifier. It does not require any prior assum

New Smart Dollar recommendations　　Source: LinkedIn　　Abhishek Thakur　　Translator: Ferguson　　"New wisdom meta-reading" This is a popular Kaggle article published by data scientist Abhishek Thakur. The author summed up his experience in more than 100 machine learning competitions, mainly from the model framework to explain the machine learning process may encounter difficulties, and give their own solutions, he also listed his usual research database, al

Https://mp.weixin.qq.com/s/JwRXBNmXBaQM2GK6BDRqMwSelected from GitHubArtur SuilinThe heart of the machine compilesParticipation: Shiyuan, Wall's, Huang Recently, Artur Suilin and other people released the Kaggle website Traffic Timing Prediction Contest first place detailed solution. They not only expose all the implementation code, but also explain the implementation model and experience in detail. The heart of the machine provides a brief o

Finished Kaggle game has been nearly five months, today to summarize, for the autumn strokes to prepare.Title: The predictive model predicts whether the user will download the app after clicking on the mobile app ad based on the click Data provided by the organizer for more than 4 days and about 200 million times. Data set Features: The volume of data is large and there are 200 million of them. The data is unbalanced and th