kaggle machine learning datasets

Yesterday I downloaded a data set for handwritten numeral recognition in Kaggle, and wanted to train a model for handwritten digit recognition through some recent learning methods. These datasets are derived from 28x28 pixel-sized handwritten digital grayscale images, where the first element of the training data is a specific handwritten number, and the remaining

in machine learning, we often encounter unbalanced datasets. In cancer data sets, for example, the number of cancer samples may be far less than the number of non-cancer samples, and in the bank's credit data set, the number of customers on schedule may be much larger than the number of customers who defaulted. For example, a very well-known German credit data s

Machine learning algorithms must act on data. The nature of data determines whether the applied machine learning algorithms are suitable, and the quality of data determines the performance of algorithms. Therefore, it is important to study and analyze data. This article, as the first part of the study data series, list

is a library that recognizes and standardizes time expressions. Stanford spied-Use patterns on the seed set to iteratively learn character entities from untagged text Stanford Topic Modeling toolbox-is a topic modeling tool for social scientists and other people who want to analyze datasets. Twitter text Java-java Implementation of the tweet processing library Mallet-Java-based statistical natural language processing, document classif

temporal tagger-sutime is a library that recognizes and standardizes time expressions. Stanford spied-usage mode on the seed set, learning character entities from unlabeled text in iterative mode Stanford topic modeling toolbox-a topic modeling tool for social scientists and other people who want to analyze datasets. Twitter text java-implemented Twitter Text Processing Library Mallet-Java-based statis

Stanford topic modeling toolbox-a topic modeling tool for social scientists and other people who want to analyze datasets. Twitter text java-implemented Twitter Text Processing Library Mallet-Java-based statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning text applicat

The sinking of the RMS Titanic is one of the very infamous shipwrecks in history. On April, 1912, during she maiden voyage, the Titanic sank after colliding with a iceberg, killing 1502 out of 2224 PA Ssengers and crew. This sensational tragedy shocked the international community and LEDs to better safety regulations for ships.One of the reasons, the shipwreck led to such loss of life is that there were not enough lifeboats for the passengers and crew. Although there was some element of luck inv

. MapReduce is free to select a node that includes a copy of a shard/block of dataThe input shard is a logical division, and the HDFS data block is the physical division of the input data. When they are consistent, they are highly efficient. In practice, however, there is never a complete agreement that records may cross the bounds of a block of data, and a compute node that processes a particular shard gets a fragment of the record from a block of data Hadoop

This column (Machine learning) includes single parameter linear regression, multiple parameter linear regression, Octave Tutorial, Logistic regression, regularization, neural network, machine learning system design, SVM (Support vector machines Support vector machine), clust

solving process clearly. Readers with time can try step by step. I do not practice, because usually the task of the laboratory is busy, but some of the ideas can be borrowed from the work. (Reading is a lot of the time to know the same question how others do, but also divergent ideas). You can feel the way the author teaches us how to learn. Unlike many of the books that give the best solutions directly, the book begins with the most basic baseline, and then gradually discovers the problem

solving process clearly. Readers with time can try step by step. I do not practice, because usually the task of the laboratory is busy, but some of the ideas can be borrowed from the work. (Reading is a lot of the time to know the same question how others do, but also divergent ideas). You can feel the way the author teaches us how to learn. Unlike many of the books that give the best solutions directly, the book begins with the most basic baseline, and then gradually discovers the problem

inspire rewards by trying and using errors to reveal specific actions. The agents can then use these rewards to understand the best state of the game and choose the next action.Quantifying the prevalence of machine learning algorithmsSome research reports (http://www.cs.uvm.edu/~icdm/algorithms/10Algorithms-08.pdf) have been done to quantify 10 of the most popular data mining algorithms. However, such a li

Author: Xyzh Link: https://www.zhihu.com/question/26726794/answer/151282052 Source: Know Copyright belongs to the author. Commercial reprint please contact the author to obtain authorization, non-commercial reprint please indicate the source. I just saw this article today about the problem. The analysis of the pros and cons of each algorithm is very pertinent. https://zhuanlan.zhihu.com/p/25327755 It was just 14 when someone did an experiment [1], comparing the actual effects of different cl

Objective:When looking for a job (IT industry), in addition to the common software development, machine learning positions can also be regarded as a choice, many computer graduate students will contact this, if your research direction is machine learning/data mining and so on, and it is very interested in, you can cons

a machine learning course at Stanford University. Take more course notes, complete course assignments as much as possible, and ask more questions. Read some books: This refers not to textbooks, but to the books listed above for beginners of programmers. Master a tool: Learn to use an analysis tool or class library, such as the python Machine

http://blog.csdn.net/zhangyingchengqi/article/details/50969064First, machine learning1. Includes nearly 400 datasets of different sizes and types for classification, regression, clustering, and referral system tasks. The data set list is located at:http://archive.ics.uci.edu/ml/2. Kaggle datasets, Kagle data sets for v