data scientist vs machine learning engineer

A bunch of online searches, and finally the links and differences between these concepts are summarized as follows: 1. Data mining: Mining is a very broad concept. It literally means digging up useful information from tons of data. This work bi (business intelligence) can be done, data analysis can be done, even market operations can be done. Using Excel to analy

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 various competitionsHttps://www.kaggle.com/com

First, the visualization method Bar chart Pie chart Box-line Diagram (box chart) Bubble chart Histogram Kernel density estimation (KDE) diagram Line Surface Chart Network Diagram Scatter chart Tree Chart Violin chart Square Chart Three-dimensional diagram Second, interactive tools Ipython, Ipython Notebook plotly Iii. Python IDE Type Pycharm, specifying a Java swing-based user interface PyDev, SWT-based

What is http://www.quora.com/What-is-data-science data science?Http://www.quora.com/How-do-I-become-a-data-scientist how can I become a data scientist?Http://www.quora.com/Data-Science/

in fact, Machine Learning has been addressing a variety of important issues. For example , in the mid-decade, people have begun to use neural networks to scan credit card transactions to find fraudulent behavior; at the end of the year,Google Use this technology for Web search. but at that time, machine learning was n

understand the task, so "save the Earth" to understand "kill all human beings." This is like a typical predictive algorithm that literally understands the task and ignores the other possibilities or the practical significance of the task.So, in January 2016, Harvard Business School professor Michael Luca, professor of economics Sendhil Mullainathan, and Cornell University professor Jon Kleinberg, published an article titled "Algorithm and Butler" in the Harvard Commercial Review. Call upon the

[Machine Learning] data preprocessing: converting data of different types into numerical values and preprocessing Data Conversion Before performing python data analysis, you must first perform

How "R" determines the machine learning algorithm that best fits the data set How "R" determines the machine learning algorithm that best fits the data setrelease time: 2016-02-25Hits: 199 Spot check (spot checking)

Course Description:This lesson focuses on the things you should be aware of in machine learning, including: Occam's Razor, sampling Bias, and Data snooping.Syllabus: 1, Occam ' s razor.2, sampling bias.3, Data snooping.1, Occam ' s Razor.Einstein once said a word: An explanation of the

Reference:http://www.52nlp.cn/python-%e7%bd%91%e9%a1%b5%e7%88%ac%e8%99%ab-%e6%96%87%e6%9c%ac%e5%a4%84%e7%90%86 -%e7%a7%91%e5%ad%a6%e8%ae%a1%e7%ae%97-%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0-%e6%95%b0%e6%8d%ae%e6%8c%96%e6%8e% 98A Python web crawler toolsetA real project must start with getting the data. Regardless of the text processing, machine learning and

change then the iteration can stop or return to ② to continue the loopExample of using the K-mans algorithm on handwritten digital image dataImportNumPy as NPImportMatplotlib.pyplot as PltImportPandas as PD fromSklearn.clusterImportKmeans#use Panda to read training datasets and test data setsDigits_train = Pd.read_csv ('Https://archive.ics.uci.edu/ml/machine-learning