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RSS订阅转载 pca learning #5
1.import numpy as npx = np.array([[-1,-1,-1],[-2,-1,-1.5],[-3,-2,-2]])x#normalize the datax_scaled = np.array(list(map(lambda y:(y-np.mean(y))/np.std(y),x.T))).Tx_scaled#Get th
2017-09-11 05:22:39
257
转载 data preprosessing
import pandas as pd#read the valuesnewdata = pd.read_csv('annotations_final.csv',sep="\t")# show the headnewdata.head(5)#show infonewdata.info()newdata.columns#concate
2017-09-10 04:47:47
279
转载 Maschine learning #4
import numpy as np#step 1 Collect Datax = np.array([[0,0,1], [0,1,1], [1,0,1], [1,1,1]])print(x) #x value and y valuey = n
2017-09-10 00:24:12
305
转载 first neuron network
from numpy import exp, array, random, dotclass NeuralNetwork(): # generate the weights def __init__(self): # Seed the random number generator, so it generates the same numb
2017-08-31 00:21:27
257
转载 prediction maschine learning
import pandas as pd --pandas: read data setfrom sklearn import linear_model -- (scikit learn maschine learning databse )import matplotlib.pyplot as plt --visualisieren model
2017-08-29 03:43:30
308
转载 How to install python3 and set up a programming on server Ubutung16.04
https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-programming-environment-on-an-ubuntu-16-04-server
2017-08-29 00:40:39
329
翻译 维数灾难
1.维数灾难（英语：curse of dimensionality，又名维度的诅咒）是一个最早由理查德·贝尔曼（Richard E. Bellman）在考虑优化问题时首次提出来的术语[1][2]，用来描述当（数学）空间维度增加时，分析和组织高维空间（通常有成百上千维），因体积指数增加而遇到各种问题场景。这样的难题在低维空间中不会遇到，如物理空间通常只用三维来建模。举例来说，10
2017-07-09 08:47:09
1794
原创 kernel (I) basic learning
1.f means Features , and this is also for hypothesis.2.kernel function is similarity function.f>0,the same clusterf3.x1,x2,two Features4.
2017-06-26 06:46:33
221
原创 python基础知识
1.安装(1)anaconda自动安装了许多包(2)在Anacoda Prompt >conda list>anaconda search -t conda tensorflow#找可安装的包>dhirschfeld/tensorflow>anaconda show dhirschfeld/tensorflow> conda install --channel https:
2017-06-19 21:32:51
281
原创 haskell learning1(2)
1.[x^2| x[z| x 50] # kann Abkürzung für oben2.[(wert,name)| wert result:[(1,'a'),(1,'b'),(2,'a'),(2,'b'),(3,'a'),(3,'b')]it :: (Enum t, Num t) => [(t, Char)]3. type MyWeirdType
2017-06-19 00:17:42
222
原创 haskell learning beginner
1.factorial n = foldl (*) 1 [1..n] Universell verwendbare Bausteine wie: foldl :: (a->b->a)->a->[b]->aa->b: functiona:type[b]:typea:Ausgabe2. stack installieren> stack new MyProj
2017-06-18 09:44:48
220
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