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Edit and run 





In [32]:



    


import tensorflow as tf



    











In [33]:



    


print("hh")



    


















    






hh

















In [34]:



    


print("hh")



    


















    






hh

















In [35]:



    


x_data = [1,2,3]
y_data = [1,2,3]



    











In [36]:



    


w = tf.Variable(tf.random_uniform([1],-1.0,1.0))
b  = tf.Variable(tf.random_uniform([1],-1.0,1.0))



    











In [37]:



    


hypothesis = w * x_data + b



    











In [38]:



    


cost = tf.reduce_mean(tf.square(hypothesis - y_data))



    











In [39]:



    


a = tf.Variable(0.1)
optimizer = tf.train.GradientDescentOptimizer(a)
train = optimizer.minimize(cost)



    











In [40]:



    


init = tf.initialize_all_variables()



    











In [41]:



    


sess = tf.Session()



    











In [42]:



    


sess.run(init)



    











In [43]:



    


for step in range(2001):
    sess.run(train)
    if step % 2 == 0:
        print(step, " | cost : ", sess.run(cost), " | w :", sess.run(w), "| b:", sess.run(b))



    


















    






0  | cost :  0.0155286  | w : [ 1.0022372] | b: [ 0.12012616]
2  | cost :  0.00129896  | w : [ 0.95872414] | b: [ 0.09532537]
4  | cost :  0.00117667  | w : [ 0.96016628] | b: [ 0.09056927]
6  | cost :  0.00106754  | w : [ 0.96205223] | b: [ 0.08626445]
8  | cost :  0.000968525  | w : [ 0.96385473] | b: [ 0.08216679]
10  | cost :  0.000878704  | w : [ 0.96557158] | b: [ 0.07826379]
12  | cost :  0.000797208  | w : [ 0.96720695] | b: [ 0.07454621]
14  | cost :  0.00072327  | w : [ 0.96876466] | b: [ 0.07100523]
16  | cost :  0.000656191  | w : [ 0.9702484] | b: [ 0.06763244]
18  | cost :  0.000595333  | w : [ 0.97166157] | b: [ 0.06441982]
20  | cost :  0.000540115  | w : [ 0.97300774] | b: [ 0.06135986]
22  | cost :  0.000490023  | w : [ 0.97428983] | b: [ 0.05844519]
24  | cost :  0.000444575  | w : [ 0.97551107] | b: [ 0.055669]
26  | cost :  0.000403343  | w : [ 0.97667432] | b: [ 0.05302469]
28  | cost :  0.000365935  | w : [ 0.97778237] | b: [ 0.05050599]
30  | cost :  0.000331996  | w : [ 0.97883767] | b: [ 0.04810691]
32  | cost :  0.000301205  | w : [ 0.9798429] | b: [ 0.04582179]
34  | cost :  0.000273272  | w : [ 0.98080039] | b: [ 0.04364523]
36  | cost :  0.000247927  | w : [ 0.98171234] | b: [ 0.04157203]
38  | cost :  0.000224933  | w : [ 0.98258108] | b: [ 0.03959736]
40  | cost :  0.00020407  | w : [ 0.98340845] | b: [ 0.03771644]
42  | cost :  0.000185146  | w : [ 0.9841966] | b: [ 0.03592491]
44  | cost :  0.000167974  | w : [ 0.9849472] | b: [ 0.03421843]
46  | cost :  0.000152395  | w : [ 0.98566228] | b: [ 0.03259307]
48  | cost :  0.000138261  | w : [ 0.98634332] | b: [ 0.03104487]
50  | cost :  0.000125438  | w : [ 0.98699206] | b: [ 0.02957021]
52  | cost :  0.000113804  | w : [ 0.98760992] | b: [ 0.0281656]
54  | cost :  0.000103248  | w : [ 0.9881984] | b: [ 0.0268277]
56  | cost :  9.36735e-05  | w : [ 0.98875898] | b: [ 0.02555338]
58  | cost :  8.49857e-05  | w : [ 0.98929298] | b: [ 0.0243396]
60  | cost :  7.71037e-05  | w : [ 0.98980153] | b: [ 0.02318343]
62  | cost :  6.99514e-05  | w : [ 0.99028599] | b: [ 0.02208221]
64  | cost :  6.34649e-05  | w : [ 0.99074745] | b: [ 0.02103332]
66  | cost :  5.75786e-05  | w : [ 0.99118692] | b: [ 0.02003422]
68  | cost :  5.22387e-05  | w : [ 0.99160552] | b: [ 0.01908257]
70  | cost :  4.73944e-05  | w : [ 0.99200433] | b: [ 0.01817616]
72  | cost :  4.2998e-05  | w : [ 0.99238408] | b: [ 0.01731276]
74  | cost :  3.90107e-05  | w : [ 0.99274588] | b: [ 0.0164904]
76  | cost :  3.53924e-05  | w : [ 0.99309045] | b: [ 0.01570709]
78  | cost :  3.21098e-05  | w : [ 0.99341863] | b: [ 0.01496098]
80  | cost :  2.91319e-05  | w : [ 0.99373132] | b: [ 0.01425034]
82  | cost :  2.643e-05  | w : [ 0.99402905] | b: [ 0.01357343]
84  | cost :  2.39786e-05  | w : [ 0.9943127] | b: [ 0.01292869]
86  | cost :  2.17554e-05  | w : [ 0.99458283] | b: [ 0.01231456]
88  | cost :  1.9737e-05  | w : [ 0.99484015] | b: [ 0.01172961]
90  | cost :  1.79068e-05  | w : [ 0.99508518] | b: [ 0.01117243]
92  | cost :  1.62456e-05  | w : [ 0.99531871] | b: [ 0.01064176]
94  | cost :  1.47393e-05  | w : [ 0.99554104] | b: [ 0.01013626]
96  | cost :  1.33722e-05  | w : [ 0.99575281] | b: [ 0.00965477]
98  | cost :  1.21322e-05  | w : [ 0.99595451] | b: [ 0.00919615]
100  | cost :  1.10068e-05  | w : [ 0.99614674] | b: [ 0.00875937]
102  | cost :  9.98628e-06  | w : [ 0.99632978] | b: [ 0.0083433]
104  | cost :  9.06002e-06  | w : [ 0.99650413] | b: [ 0.00794699]
106  | cost :  8.21959e-06  | w : [ 0.99667019] | b: [ 0.00756951]
108  | cost :  7.45714e-06  | w : [ 0.99682832] | b: [ 0.00720993]
110  | cost :  6.7656e-06  | w : [ 0.996979] | b: [ 0.00686747]
112  | cost :  6.13818e-06  | w : [ 0.99712253] | b: [ 0.00654125]
114  | cost :  5.5687e-06  | w : [ 0.9972592] | b: [ 0.00623054]
116  | cost :  5.05257e-06  | w : [ 0.99738932] | b: [ 0.00593455]
118  | cost :  4.58364e-06  | w : [ 0.99751341] | b: [ 0.00565269]
120  | cost :  4.15864e-06  | w : [ 0.99763149] | b: [ 0.00538418]
122  | cost :  3.7731e-06  | w : [ 0.99774396] | b: [ 0.00512841]
124  | cost :  3.42319e-06  | w : [ 0.99785113] | b: [ 0.00488481]
126  | cost :  3.10563e-06  | w : [ 0.99795324] | b: [ 0.00465277]
128  | cost :  2.81758e-06  | w : [ 0.99805051] | b: [ 0.00443177]
130  | cost :  2.55635e-06  | w : [ 0.99814314] | b: [ 0.00422127]
132  | cost :  2.31921e-06  | w : [ 0.99823129] | b: [ 0.00402072]
134  | cost :  2.10397e-06  | w : [ 0.99831527] | b: [ 0.00382971]
136  | cost :  1.90899e-06  | w : [ 0.99839532] | b: [ 0.00364783]
138  | cost :  1.73187e-06  | w : [ 0.99847156] | b: [ 0.00347455]
140  | cost :  1.57138e-06  | w : [ 0.99854416] | b: [ 0.00330951]
142  | cost :  1.42552e-06  | w : [ 0.9986133] | b: [ 0.0031523]
144  | cost :  1.29324e-06  | w : [ 0.99867916] | b: [ 0.00300257]
146  | cost :  1.17332e-06  | w : [ 0.99874192] | b: [ 0.00285996]
148  | cost :  1.06455e-06  | w : [ 0.99880165] | b: [ 0.00272411]
150  | cost :  9.65759e-07  | w : [ 0.99885857] | b: [ 0.0025947]
152  | cost :  8.76268e-07  | w : [ 0.99891287] | b: [ 0.00247148]
154  | cost :  7.94864e-07  | w : [ 0.99896443] | b: [ 0.00235405]
156  | cost :  7.21187e-07  | w : [ 0.99901366] | b: [ 0.00224225]
158  | cost :  6.54278e-07  | w : [ 0.99906045] | b: [ 0.00213571]
160  | cost :  5.93662e-07  | w : [ 0.9991051] | b: [ 0.00203428]
162  | cost :  5.38588e-07  | w : [ 0.99914765] | b: [ 0.00193768]
164  | cost :  4.88726e-07  | w : [ 0.99918813] | b: [ 0.00184564]
166  | cost :  4.43339e-07  | w : [ 0.99922663] | b: [ 0.00175796]
168  | cost :  4.02163e-07  | w : [ 0.99926341] | b: [ 0.00167446]
170  | cost :  3.64887e-07  | w : [ 0.99929839] | b: [ 0.00159493]
172  | cost :  3.31092e-07  | w : [ 0.99933171] | b: [ 0.00151919]
174  | cost :  3.00427e-07  | w : [ 0.99936342] | b: [ 0.00144703]
176  | cost :  2.72522e-07  | w : [ 0.9993937] | b: [ 0.00137831]
178  | cost :  2.47277e-07  | w : [ 0.99942249] | b: [ 0.00131284]
180  | cost :  2.24307e-07  | w : [ 0.99944991] | b: [ 0.00125049]
182  | cost :  2.03485e-07  | w : [ 0.99947602] | b: [ 0.0011911]
184  | cost :  1.84606e-07  | w : [ 0.99950087] | b: [ 0.00113453]
186  | cost :  1.67503e-07  | w : [ 0.99952465] | b: [ 0.00108066]
188  | cost :  1.52023e-07  | w : [ 0.99954718] | b: [ 0.0010293]
190  | cost :  1.37885e-07  | w : [ 0.9995687] | b: [ 0.00098043]
192  | cost :  1.25112e-07  | w : [ 0.9995892] | b: [ 0.00093387]
194  | cost :  1.13497e-07  | w : [ 0.9996087] | b: [ 0.00088951]
196  | cost :  1.0298e-07  | w : [ 0.99962729] | b: [ 0.00084726]
198  | cost :  9.34352e-08  | w : [ 0.99964499] | b: [ 0.00080702]
200  | cost :  8.47551e-08  | w : [ 0.99966192] | b: [ 0.00076869]
202  | cost :  7.6907e-08  | w : [ 0.9996779] | b: [ 0.00073216]
204  | cost :  6.97812e-08  | w : [ 0.99969327] | b: [ 0.00069741]
206  | cost :  6.33097e-08  | w : [ 0.99970776] | b: [ 0.00066426]
208  | cost :  5.74222e-08  | w : [ 0.99972165] | b: [ 0.00063272]
210  | cost :  5.2086e-08  | w : [ 0.99973488] | b: [ 0.00060266]
212  | cost :  4.72542e-08  | w : [ 0.99974751] | b: [ 0.00057405]
214  | cost :  4.29039e-08  | w : [ 0.99975944] | b: [ 0.00054677]
216  | cost :  3.8906e-08  | w : [ 0.99977094] | b: [ 0.00052082]
218  | cost :  3.53019e-08  | w : [ 0.99978179] | b: [ 0.00049606]
220  | cost :  3.2011e-08  | w : [ 0.99979216] | b: [ 0.00047249]
222  | cost :  2.90554e-08  | w : [ 0.99980205] | b: [ 0.00045006]
224  | cost :  2.63682e-08  | w : [ 0.99981147] | b: [ 0.00042869]
226  | cost :  2.38994e-08  | w : [ 0.99982035] | b: [ 0.0004083]
228  | cost :  2.17e-08  | w : [ 0.99982893] | b: [ 0.00038892]
230  | cost :  1.96656e-08  | w : [ 0.99983704] | b: [ 0.00037042]
232  | cost :  1.78612e-08  | w : [ 0.99984479] | b: [ 0.00035284]
234  | cost :  1.61949e-08  | w : [ 0.99985218] | b: [ 0.00033609]
236  | cost :  1.46995e-08  | w : [ 0.99985921] | b: [ 0.00032012]
238  | cost :  1.33308e-08  | w : [ 0.99986595] | b: [ 0.00030492]
240  | cost :  1.21027e-08  | w : [ 0.99987227] | b: [ 0.00029042]
242  | cost :  1.09813e-08  | w : [ 0.99987829] | b: [ 0.00027661]
244  | cost :  9.9563e-09  | w : [ 0.99988413] | b: [ 0.00026349]
246  | cost :  9.0293e-09  | w : [ 0.99988961] | b: [ 0.00025097]
248  | cost :  8.19158e-09  | w : [ 0.99989486] | b: [ 0.00023905]
250  | cost :  7.43952e-09  | w : [ 0.99989992] | b: [ 0.00022771]
252  | cost :  6.7483e-09  | w : [ 0.99990457] | b: [ 0.00021684]
254  | cost :  6.12498e-09  | w : [ 0.99990916] | b: [ 0.00020655]
256  | cost :  5.56061e-09  | w : [ 0.99991339] | b: [ 0.0001967]
258  | cost :  5.02945e-09  | w : [ 0.99991757] | b: [ 0.00018739]
260  | cost :  4.56229e-09  | w : [ 0.99992144] | b: [ 0.0001785]
262  | cost :  4.1492e-09  | w : [ 0.9999252] | b: [ 0.00017004]
264  | cost :  3.76291e-09  | w : [ 0.99992877] | b: [ 0.00016196]
266  | cost :  3.41703e-09  | w : [ 0.99993217] | b: [ 0.00015427]
268  | cost :  3.10185e-09  | w : [ 0.99993533] | b: [ 0.00014692]
270  | cost :  2.80724e-09  | w : [ 0.99993843] | b: [ 0.00013994]
272  | cost :  2.54846e-09  | w : [ 0.99994135] | b: [ 0.00013331]
274  | cost :  2.31349e-09  | w : [ 0.99994415] | b: [ 0.00012697]
276  | cost :  2.10218e-09  | w : [ 0.99994677] | b: [ 0.00012094]
278  | cost :  1.90538e-09  | w : [ 0.99994928] | b: [ 0.0001152]
280  | cost :  1.72871e-09  | w : [ 0.99995166] | b: [ 0.00010972]
282  | cost :  1.56993e-09  | w : [ 0.99995399] | b: [ 0.00010454]
284  | cost :  1.42004e-09  | w : [ 0.99995619] | b: [  9.95719092e-05]
286  | cost :  1.29033e-09  | w : [ 0.99995822] | b: [  9.48353263e-05]
288  | cost :  1.16737e-09  | w : [ 0.99996024] | b: [  9.03530599e-05]
290  | cost :  1.06425e-09  | w : [ 0.99996215] | b: [  8.60774162e-05]
292  | cost :  9.63254e-10  | w : [ 0.99996394] | b: [  8.19766210e-05]
294  | cost :  8.7626e-10  | w : [ 0.99996561] | b: [  7.80586051e-05]
296  | cost :  7.92383e-10  | w : [ 0.99996728] | b: [  7.43710625e-05]
298  | cost :  7.1996e-10  | w : [ 0.99996877] | b: [  7.08186271e-05]
300  | cost :  6.54822e-10  | w : [ 0.99997032] | b: [  6.74728217e-05]
302  | cost :  5.92801e-10  | w : [ 0.99997175] | b: [  6.42780142e-05]
304  | cost :  5.35792e-10  | w : [ 0.99997306] | b: [  6.12024160e-05]
306  | cost :  4.85026e-10  | w : [ 0.99997437] | b: [  5.82937064e-05]
308  | cost :  4.44122e-10  | w : [ 0.99997556] | b: [  5.55201041e-05]
310  | cost :  4.00353e-10  | w : [ 0.99997675] | b: [  5.28974997e-05]
312  | cost :  3.65527e-10  | w : [ 0.99997783] | b: [  5.03941046e-05]
314  | cost :  3.32913e-10  | w : [ 0.9999789] | b: [  4.80099188e-05]
316  | cost :  2.99792e-10  | w : [ 0.99997985] | b: [  4.57131537e-05]
318  | cost :  2.71982e-10  | w : [ 0.99998087] | b: [  4.35514885e-05]
320  | cost :  2.48463e-10  | w : [ 0.99998182] | b: [  4.15010873e-05]
322  | cost :  2.22926e-10  | w : [ 0.9999826] | b: [  3.94983726e-05]
324  | cost :  2.02614e-10  | w : [ 0.99998343] | b: [  3.76387106e-05]
326  | cost :  1.85328e-10  | w : [ 0.9999842] | b: [  3.58664656e-05]
328  | cost :  1.68356e-10  | w : [ 0.99998498] | b: [  3.41736923e-05]
330  | cost :  1.52662e-10  | w : [ 0.99998564] | b: [  3.25365509e-05]
332  | cost :  1.37675e-10  | w : [ 0.99998641] | b: [  3.10265677e-05]
334  | cost :  1.26102e-10  | w : [ 0.99998701] | b: [  2.95324789e-05]
336  | cost :  1.13995e-10  | w : [ 0.99998766] | b: [  2.81496505e-05]
338  | cost :  1.02962e-10  | w : [ 0.9999882] | b: [  2.67827163e-05]
340  | cost :  9.33179e-11  | w : [ 0.99998879] | b: [  2.55190989e-05]
342  | cost :  8.52509e-11  | w : [ 0.99998933] | b: [  2.43190589e-05]
344  | cost :  7.7217e-11  | w : [ 0.99998987] | b: [  2.31746508e-05]
346  | cost :  6.96e-11  | w : [ 0.99999028] | b: [  2.20302409e-05]
348  | cost :  6.35746e-11  | w : [ 0.99999076] | b: [  2.09970949e-05]
350  | cost :  5.75634e-11  | w : [ 0.99999118] | b: [  2.00036848e-05]
352  | cost :  5.18649e-11  | w : [ 0.9999916] | b: [  1.90500105e-05]
354  | cost :  4.66732e-11  | w : [ 0.99999201] | b: [  1.81519663e-05]
356  | cost :  4.26373e-11  | w : [ 0.99999237] | b: [  1.72936579e-05]
358  | cost :  3.95251e-11  | w : [ 0.99999279] | b: [  1.64830344e-05]
360  | cost :  3.55082e-11  | w : [ 0.99999309] | b: [  1.56962542e-05]
362  | cost :  3.12639e-11  | w : [ 0.99999344] | b: [  1.49492098e-05]
364  | cost :  2.90328e-11  | w : [ 0.99999374] | b: [  1.42339541e-05]
366  | cost :  2.64701e-11  | w : [ 0.99999404] | b: [  1.35425398e-05]
368  | cost :  2.34053e-11  | w : [ 0.9999944] | b: [  1.29226510e-05]
370  | cost :  2.17142e-11  | w : [ 0.99999464] | b: [  1.22868678e-05]
372  | cost :  1.92747e-11  | w : [ 0.99999487] | b: [  1.16987685e-05]
374  | cost :  1.82515e-11  | w : [ 0.99999511] | b: [  1.11583531e-05]
376  | cost :  1.61104e-11  | w : [ 0.99999529] | b: [  1.06020425e-05]
378  | cost :  1.46514e-11  | w : [ 0.99999553] | b: [  1.00934158e-05]
380  | cost :  1.32682e-11  | w : [ 0.99999577] | b: [  9.64042010e-06]
382  | cost :  1.19371e-11  | w : [ 0.99999601] | b: [  9.18742444e-06]
384  | cost :  1.07292e-11  | w : [ 0.99999619] | b: [  8.75032401e-06]
386  | cost :  9.80075e-12  | w : [ 0.9999963] | b: [  8.31322359e-06]
388  | cost :  9.08074e-12  | w : [ 0.99999648] | b: [  7.93970139e-06]
390  | cost :  8.00071e-12  | w : [ 0.99999666] | b: [  7.55823157e-06]
392  | cost :  7.67386e-12  | w : [ 0.99999684] | b: [  7.21649849e-06]
394  | cost :  6.55594e-12  | w : [ 0.99999696] | b: [  6.85887062e-06]
396  | cost :  6.06803e-12  | w : [ 0.99999714] | b: [  6.56482098e-06]
398  | cost :  5.36697e-12  | w : [ 0.99999726] | b: [  6.23898222e-06]
400  | cost :  5.09696e-12  | w : [ 0.99999738] | b: [  5.93698542e-06]
402  | cost :  4.58537e-12  | w : [ 0.9999975] | b: [  5.65883010e-06]
404  | cost :  4.05957e-12  | w : [ 0.99999762] | b: [  5.40451720e-06]
406  | cost :  3.58114e-12  | w : [ 0.99999774] | b: [  5.13430905e-06]
408  | cost :  3.51008e-12  | w : [ 0.99999779] | b: [  4.88794331e-06]
410  | cost :  3.14534e-12  | w : [ 0.99999797] | b: [  4.68926146e-06]
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1900  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
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1904  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
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1914  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1916  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1918  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1920  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1922  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1924  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1926  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1928  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1930  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1932  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1934  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1936  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1938  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1940  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1942  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1944  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1946  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1948  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1950  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1952  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1954  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1956  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1958  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1960  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1962  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1964  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1966  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1968  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1970  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1972  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1974  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1976  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1978  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1980  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1982  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1984  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1986  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1988  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1990  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1992  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1994  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1996  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
1998  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]
2000  | cost :  0.0  | w : [ 1.] | b: [  5.59946614e-08]

















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Content source: JaeGyu/PythonEx_1

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