{"id":1722,"date":"2024-09-20T13:40:22","date_gmt":"2024-09-20T05:40:22","guid":{"rendered":"http:\/\/blog.ndsc.tw\/?p=1722"},"modified":"2024-09-28T17:39:56","modified_gmt":"2024-09-28T09:39:56","slug":"%e3%80%90ai%e6%b7%b1%e5%ba%a6%e5%ad%b8%e7%bf%92%e8%88%87%e8%a6%96%e8%a6%ba%e8%be%a8%e8%ad%98%e6%87%89%e7%94%a8%e7%8f%ad%e7%ac%ac01%e6%9c%9f%e3%80%91-%e5%98%89%e7%be%a9%e7%8f%ad","status":"publish","type":"post","link":"http:\/\/blog.ndsc.tw\/?p=1722","title":{"rendered":"\u3010AI\u6df1\u5ea6\u5b78\u7fd2\u8207\u8996\u89ba\u8fa8\u8b58\u61c9\u7528\u73ed\u7b2c01\u671f\u3011_\u5609\u7fa9\/\u53f0\u5317\u73ed_\u52de\u52d5\u90e8\u7522\u696d\u4eba\u624d\u6295\u8cc7\u8ab2\u7a0b_\u7d50\u8a13\u8b49\u66f8_\u52de\u5de5\u9032\u4fee\u88dc\u52a98\u6210~\u5168\u984d_\u5609\u7fa9\u4e2d\u6b63\u5927\u5b78\/\u53f0\u5317\u5e2b\u7bc4\u5927\u5b78\u4e0a\u8ab2_\u71b1\u70c8\u62db\u751f\u4e2d"},"content":{"rendered":"\n


\u5168\u4e16\u754c\u6b63\u5728\u8d70\u5411\u4e00\u500b\u5d84\u65b0\u7684\u6642\u4ee3\uff0c\u5de5\u696d\u793e\u6703\u5c07\u51fa\u73fe\u91cd\u5927\u7684\u8b8a\u9769\uff0c\u5de5\u5ee0\u7684\u88fd\u9020\u5c07\u8d70\u5411\u5168\u65b0\u7684\u667a\u6167\u88fd\u9020\u65b0\u6a21\u5f0f\uff0c\u751f\u6d3b\u5bb6\u5c45\u4e5f\u5c07\u9032\u6b65\u5230\u667a\u6167\u5bb6\u5c45\u3002\u70ba\u4f55\u6642\u4ee3\u9032\u6b65\u5982\u6b64\u4e4b\u5feb\uff0c\u9019\u4ee4\u6211\u5011\u5c0d\u672a\u4f86\u5145\u6eff\u4e86\u63a2\u7d22\u7684\u71b1\u60c5\uff0c\u5168\u4e16\u754c\u90fd\u9762\u81e8AI\u6280\u8853\u7a81\u7834\u5c0e\u81f4\u76844.0\u7684\u7522\u696d\u9769\u547d\u3002\u901a\u8a0a\u6280\u8853\u5f9e4G\u6b65\u51655G\u3001GPU\u7684\u554f\u4e16\u3001\u52a0\u4e0a\u6f14\u7b97\u6cd5\u7684\u7a81\u7834\uff0c\u9019\u4e09\u500b\u8981\u7d20\uff0c\u4fc3\u6210\u4e86AI\u6642\u4ee3\u7684\u5230\u4f86\u3002<\/strong><\/p>\n\n\n\n

\u6df1\u5ea6\u5b78\u7fd2\u662fAI\u4eba\u5de5\u667a\u6167\u4e2d\u7684\u4e00\u7a2e\u65b9\u6cd5\uff0c\u53ef\u6307\u5c0e\u96fb\u8166\u4ee5\u53d7\u4eba\u8166\u555f\u767c\u7684\u65b9\u5f0f\u4f86\u8655\u7406\u8cc7\u6599\u3002\u6df1\u5ea6\u5b78\u7fd2\u6a21\u578b\u53ef\u8b58\u5225\u5716\u7247\u3001\u6587\u5b57\u3001\u8072\u97f3\u548c\u5176\u4ed6\u8cc7\u6599\u7684\u8907\u96dc\u6a21\u5f0f\uff0c\u85c9\u6b64\u7522\u751f\u66f4\u6e96\u78ba\u7684\u6d1e\u5bdf\u548c\u9810\u6e2c\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528\u6df1\u5ea6\u5b78\u7fd2\u65b9\u6cd5\u5c07\u901a\u5e38\u9700\u8981\u4eba\u985e\u667a\u6167\u7684\u4efb\u52d9\u81ea\u52d5\u5316\uff0c\u4f8b\u5982\u63cf\u8ff0\u5f71\u50cf\u6216\u5c07\u8072\u97f3\u6a94\u6848\u8f49\u9304\u70ba\u6587\u5b57\u3002 
\u6df1\u5ea6\u5b78\u7fd2\u662f\u6a5f\u5668\u5b78\u7fd2\u7684\u9032\u5316\u3002\u800c\u6a5f\u5668\u5b78\u7fd2\uff0c\u642d\u914d\u5f71\u50cf\u8fa8\u8b58\u6240\u4ef0\u8cf4\u7684\u6a5f\u5668\u8996\u89ba\u3002\u6a5f\u5668\u5b78\u7fd2\uff0c\u662f\u96fb\u8166\u548c\u651d\u5f71\u6a5f\u7d50\u5408\uff0c\u5f9e\u5f71\u50cf\u548c\u5f71\u7247\u4e2d\u64f7\u53d6\u8cc7\u8a0a\u548c\u6d1e\u5bdf\u7684\u529f\u80fd\u3002\u96fb\u8166\u53ef\u4ee5\u4f7f\u7528\u6df1\u5ea6\u5b78\u7fd2\u6280\u8853\uff0c\u5f9e\u800c\u4ee5\u8207\u4eba\u985e\u76f8\u540c\u7684\u65b9\u5f0f\u7406\u89e3\u5716\u50cf\u3002\u96fb\u8166\u8996\u89ba\u6709\u591a\u7a2e\u61c9\u7528\uff0c\u4f8b\u5982\uff1a\u5167\u5bb9\u5be9\u6838\uff0c\u53ef\u81ea\u52d5\u5f9e\u5f71\u50cf\u548c\u5f71\u7247\u5c01\u5b58\u4e2d\u79fb\u9664\u4e0d\u5b89\u5168\u6216\u4e0d\u7576\u7684\u5167\u5bb9\uff1b\u53c8\u5982\u81c9\u90e8\u8b58\u5225\uff0c\u53ef\u8b58\u5225\u81c9\u90e8\uff0c\u4e26\u8b58\u5225\u775c\u773c\u3001\u773c\u93e1\u548c\u9762\u90e8\u6bdb\u9aee\u7b49\u5c6c\u6027\uff1b\u518d\u5982\u5f71\u50cf\u5206\u985e\uff0c\u53ef\u8b58\u5225\u54c1\u724c\u6a19\u8a8c\u3001\u670d\u88dd\u3001\u5b89\u5168\u88dd\u5099\u548c\u5176\u4ed6\u5f71\u50cf\u8a73\u7d30\u8cc7\u8a0a\u3002<\/strong>

\u672c\u8ab2\u7a0b\u7531\u524d\u570b\u9632\u90e8\u96f2\u8c79\u7532\u8eca\u7684\u7814\u767c\u7e3d\u5de5\u7a0b\u5e2b\u674e\u5929\u660e\u6559\u6388\u548c\u53f0\u5927\u7cbe\u5bc6\u88fd\u9020\u5be6\u9a57\u5ba4\u535a\u58eb\u73ed\u5c08\u653bAI\u8207\u81ea\u52d5\u5149\u5b78\u6aa2\u6e2cAOI\u6574\u5408\u61c9\u7528\u7684\u5ed6\u662d\u660c\u5c08\u5bb6\uff0c\u5171\u540c\u6388\u8ab2\u3002\u674e\u5929\u660e\u6559\u6388\u7559\u82f1\u66fc\u5fb9\u65af\u7279\u5927\u5b78\u96fb\u8166\u79d1\u5b78\u535a\u58eb\uff0c\u9577\u671f\u5f9e\u4e8bAI\u7684\u7814\u7a76\u3002<\/strong><\/p>\n\n\n\n

<\/p>\n\n\n\n

\u672c\u8ab2\u7a0b\u5b78\u7fd2\u91cd\u9ede\u5305\u542b\uff1a
1. \u7522\u696d\u8abf\u7814\u5206\u6790\u7406\u8ad6(\u4e00)\uff1a\u751f\u547d\u9031\u671f\u3001\u50f9\u503c\u93c8\u8207\u4e94\u529b\u5206\u6790\u3002\u61c9\u7528\u5be6\u4f8b\u89e3\u8aaa\uff1a\u85dd\u8853\u8207\u4eba\u6587\u7522\u696d\u3001AI\u6df1\u5ea6\u5b78\u7fd2\u8207\u8996\u89ba\u8fa8\u8b58\u7522\u696d
2. \u7522\u696d\u8abf\u7814\u5206\u6790\u7406\u8ad6(\u4e8c)\uff1a\u7af6\u722d\u7b56\u7565\u3001KSF\u8207\u6280\u8853\u7522\u54c1\u751f\u547d\u9031\u671f\u3002\u61c9\u7528\u5be6\u4f8b\u89e3\u8aaa\uff1a\u85dd\u8853\u8207\u4eba\u6587\u7522\u696d\u3001AI\u6df1\u5ea6\u5b78\u7fd2\u8207\u8996\u89ba\u8fa8\u8b58\u7522\u696d
3. AI\u8996\u89ba\u8fa8\u8b58\u8207\u61c9\u7528\u7522\u696d\u4e4b\u884c\u8077\u696d\u5206\u6790\uff1a\u6280\u8853\u73fe\u6cc1\u3001\u7522\u696d\u73fe\u6cc1\u3001\u8077\u6daf\u767c\u5c55
4. AI\u8996\u89ba\u5f71\u50cf\u8fa8\u8b58\u6aa2\u6e2c\u4e4b\u539f\u7406\uff1a\u7455\u75b5\u5f71\u50cf\u5316\u3001\u6ffe\u9664\u96dc\u8a0a\u8207\u7279\u5fb5\u5f37\u5316\u3001\u5f71\u50cf\u6aa2\u6e2c\u8207\u5f71\u50cf\u91cf\u6e2c
5. ANN\u985e\u795e\u7d93\u7db2\u8def\u539f\u7406: -AI\u667a\u6167\u63a7\u5236\u539f\u7406 -\u4eba\u985e\u8166\u795e\u7d93\u5143\u904b\u4f5c\u57fa\u672c\u6a21\u5f0f -\u55ae\u4e00\u795e\u7d93\u7d30\u80de\u611f\u77e5\u539f\u7406
6. Perceptron Learning\u7dda\u6027\u5206\u985e\u6cd5: -\u8166\u795e\u7d93\u7d30\u80de\u53cd\u61c9\u6a21\u5f0f(Activation Function) -\u55ae\u4e00\u795e\u7d93\u7d30\u80de\u5b78\u7fd2\u6cd5 -\u7dda\u6027\u53ef\u5206\u5272\u554f\u984c\u4e4b\u5b78\u7fd2
7. MLP\u591a\u5c64\u795e\u7d93\u7d30\u80de\u611f\u77e5\u5668(\u4e00): -\u975e\u7dda\u6027\u53ef\u5206\u5272\u554f\u984c\u4e4b\u5b78\u7fd2 -\u591a\u5c64\u795e\u7d93\u7d30\u80de\u7d44\u7e54\u67b6\u69cb -\u975e\u7dda\u6027\u53cd\u61c9\u65b9\u7a0b\u5f0f\u4e4b\u61c9\u7528
8. MLP\u591a\u5c64\u795e\u7d93\u611f\u77e5\u5668(\u4e8c): -\u591a\u5c64\u795e\u7d93\u7d30\u80de\u4e4b\u8a0a\u865f\u50b3\u905e\u65b9\u5f0f -\u975e\u7dda\u6027\u53cd\u61c9\u65b9\u7a0b\u5f0f\u4e4b\u61c9\u7528(Sigmoid function)
-\u8aa4\u5dee\u5012\u50b3\u905e\u6cd5(Error-back propagation) -\u68af\u5ea6\u4e0b\u964d\u6cd5(Gradient decent)
9. AI \u667a\u6167\u63a7\u5236\u6280\u8853\u5c0e\u5165\u5be6\u52d9(\u4e00): -\u6a5f\u5668\u4eba\u5c0e\u5165AI\u4e4b\u64cd\u4f5c\u6a21\u5f0f -AI\u667a\u6167\u6a5f\u5668\u4eba\u5b78\u7fd2\u907f\u969c\u884c\u70ba -AI\u667a\u6167\u6a5f\u5668\u4eba\u5b78\u7fd2\u6cbf\u7246\u884c\u70ba\u6a21\u5f0f
10. AI \u667a\u6167\u63a7\u5236\u6280\u8853\u5c0e\u5165\u5be6\u52d9(\u4e8c): -\u5c0e\u5165ANN\u795e\u7d93\u5143\u7d44\u7e54\u67b6\u69cb\u4e4b\u5be6\u52d9\u63a2\u8a0e -\u5b78\u7fd2\u901f\u7387(learning step)\u5c0d\u5b78\u7fd2\u6e96\u78ba\u5ea6\u4e4b\u5f71\u97ff -\u5982\u4f55\u64f7\u53d6\u8a13\u7df4\u8cc7\u6599 -\u5982\u4f55\u907f\u514d\u904e\u5ea6\u5b78\u7fd2(over training)
11. AI\u667a\u6167\u5f71\u50cf\u8fa8\u8b58\u6280\u8853(\u4e00): -\u6578\u4f4d\u5f71\u50cf\u4e4b\u5b9a\u7fa9 -\u89e3\u6790\u5ea6 -RGB\u8207\u8a18\u61b6\u9ad4
12. I\u667a\u6167\u5f71\u50cf\u8fa8\u8b58\u6280\u8853(\u4e8c): -\u5c0e\u5165AI\u524d\u6240\u9700\u4e4b\u6578\u4f4d\u5f71\u50cf\u8655\u88e1\u6280\u8853 -Histogram\u5f71\u50cf\u5f37\u5316 -\u5e7e\u4f55\u7e2e\u653e\u8207\u96dc\u8a0a\u53bb\u9664 -\u5f71\u50cf\u5c0b\u908a(Edge finding)\u6280\u8853\u8207\u61c9\u7528
13. Python\u7a0b\u5f0f\u8a9e\u8a00\u57fa\u790e(\u4e00): -\u57fa\u672c\u8a9e\u6cd5\u4ecb\u7d39 -\u57fa\u790e\u6307\u4ee4\u4ecb\u7d39\u8207\u61c9\u7528\u6f14\u7df4
14. Python\u7a0b\u5f0f\u8a9e\u8a00\u57fa\u790e(\u4e8c): -\u8ff4\u5708\u8207\u5224\u65b7\u6307\u4ee4\u4e4b\u61c9\u7528\u6f14\u7df4 -\u5716\u5f62\u7e6a\u88fd\u6307\u4ee4\u4ecb\u7d39\u8207\u61c9\u7528\u6f14\u7df4
15. Perceptron Learning (AND\/OR logic): -\u4f7f\u7528Python \u8a9e\u8a00\u7de8\u64b0\u53ef\u5b78\u7fd2\u7dda\u6027\u908f\u8f2f\u53cd\u61c9(AND\/OR)\u4e4b\u96fb\u8166\u7a0b\u5f0f
16. MLP Learning (Exclusive OR): -\u4f7f\u7528Python \u8a9e\u8a00\u7de8\u64b0\u53ef\u5b78\u7fd2\u975e\u7dda\u6027\u908f\u8f2f\u53cd\u61c9(XOR)\u4e4b\u96fb\u8166\u7a0b\u5f0f
17. Python \u958b\u6e90\u7a0b\u5f0f\u5eab\u4e4b\u61c9\u7528Open source application in Python(\u4e00): -\u5c0e\u5165TensorFlow\u8a2d\u5b9a\u8207\u5b89\u88dd -\u5c0e\u5165Keras\u8a2d\u5b9a\u8207\u5b89\u88dd
18. Python \u958b\u6e90\u7a0b\u5f0f\u5eab\u4e4b\u61c9\u7528Open source application in Python(\u4e8c): -\u4f7f\u7528TensorFlow\u8207 Keras \u57f7\u884cAI\u5b78\u7fd2\u4e4b\u6f14\u7df4\u5be6\u4f5c -\u5982\u4f55\u8a2d\u5b9a\u8f38\u5165\u5c64\u3001\u96b1\u85cf\u5c64\u3001\u8f38\u51fa\u5c64<\/strong>
<\/p>\n\n\n\n

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\u52de\u52d5\u90e8\u88dc\u52a9\u5728\u8077\u52de\u5de5\u9032\u4fee80~100%\u5b78\u8cbb\uff0c\u4e09\u5e74\u4e03\u842c\u2027\u5b78\u7fd2\u4e0d\u65b7
\u3010AI\u6df1\u5ea6\u5b78\u7fd2\u8207\u8996\u89ba\u8fa8\u8b58\u61c9\u7528\u73ed\u7b2c01\u671f\u3011
\u8ab2\u7a0b\u4ecb\u7d39\uff1a\u667a\u80fd\u5149\u5b78\u61c9\u7528\u4ecb\u7d39\u3001AI\u667a\u6167\u5f71\u50cf\u8fa8\u8b58\u6280\u8853\u3001Python\u7a0b\u5f0f\u7de8\u5beb\u61c9\u7528\u3001\u667a\u80fd\u5149\u5b78\u6aa2\u6e2c\u539f\u7406\u3001AI\u667a\u6167\u63a7\u5236\u4ecb\u7d39
\u8b1b\u5e2b\uff1a\u674e\u5929\u660e\u8001\u5e2b(\u82f1\u570b\u66fc\u5fb9\u65af\u7279\u5927\u5b78\u96fb\u8166\u79d1\u5b78\u535a\u58eb)\u3001\u5ed6\u662d\u660c\u8001\u5e2b(\u667a\u6cf0\u79d1\u6280AI\u8207AOI\u5c08\u6848\u7814\u7a76\u54e1)
\u4e0a\u8ab2\u8cbb\u7528\uff1a10390\u5143(\u5177\u52de\u4fdd\u5728\u4fdd\u8eab\u5206\u53ef\u88dc\u52a9\u5b78\u8cbb80%~100%)
\u793e\u5718\u6cd5\u4eba\u53f0\u7063\u793e\u5340\u85dd\u8853\u8207\u4eba\u6587\u767c\u5c55\u5354\u6703\u4e3b\u8fa6(TTQS\u9285\u724c\u8a13\u7df4\u6a5f\u69cb)
\u6d3d\u8a62\u96fb\u8a71\uff1a 02-27082770 \u9b4f\u5148\u751f
\u203b\u9700\u70ba\u300c\u53f0\u7063\u5c31\u696d\u901a\u300d\u6703\u54e1\u65b9\u53ef\u5831\u540d\u8ab2\u7a0b\uff0c\u5c1a\u672a\u52a0\u5165\u6703\u54e1\u8005\u8acb\u5148\u9032\u5165\u4e0b\u65b9\u7db2\u5740\u5f8c\uff0c\u9ede\u9078\u53f3\u4e0a\u65b9\u300c\u8a3b\u518a\u300d\u52a0\u5165\u6703\u54e1\u3002
https:\/\/job.taiwanjobs.gov.tw\/Internet\/Index\/Index.aspx<\/a>

********************\u5609\u7fa9\u73ed\u8a0a\u606f*******************
\u8ab2\u7a0b\u4ee3\u78bc\uff1a157022
\u6642\u9593\uff1a113\/10\/06~12\/01(\u6bcf\u5468\u65e509:00~12:00\u300113:00~17:00) \u4e0a\u8ab29\u5929\u5171\u8a0863\u5c0f\u6642
\u5730\u9ede\uff1a\u6e05\u6c5f\u63a8\u5ee3\u6559\u80b2\u5927\u6a13203\u6559\u5ba4(\u5609\u7fa9\u5e02\u4e16\u8ce2\u8def\u56db\u6bb5120\u865f)
\u5831\u540d\u7db2\u5740\uff1ahttps:\/\/is.gd\/wVLru1<\/a><\/p>\n\n\n\n

Youtube\u5ee3\u544a\u5f71\u7247\u00a0https:\/\/youtu.be\/WLikh-3bt-Y<\/a>

*************\u53f0\u5317\u73ed\u8a0a\u606f***************
\u8ab2\u7a0b\u4ee3\u78bc\uff1a157257\u00a0\u00a0
\u958b\u59cb\u5831\u540d10\/25\u4e2d\u534812:00
\u6642\u9593\uff1a11\/24~114\/1\/19(\u5468\u65e509:00~17:00) \u8a0863\u5c0f\u6642
\u5730\u9ede\uff1a\u570b\u7acb\u5e2b\u7bc4\u5927\u5b78 \u516c\u9928\u6821\u5340\u7814\u7a76\u5927\u6a13S302(\u81fa\u5317\u5e02\u6587\u5c71\u5340\u6c40\u5dde\u8def\uff14\u6bb588\u865f)
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\u5168\u4e16\u754c\u6b63\u5728\u8d70\u5411\u4e00\u500b\u5d84\u65b0\u7684\u6642\u4ee3\uff0c\u5de5\u696d\u793e\u6703\u5c07\u51fa\u73fe\u91cd\u5927\u7684\u8b8a\u9769\uff0c\u5de5\u5ee0\u7684\u88fd\u9020\u5c07\u8d70\u5411\u5168\u65b0\u7684\u667a… Continue Reading →<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[51,1],"tags":[],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p4dxA5-rM","_links":{"self":[{"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=\/wp\/v2\/posts\/1722"}],"collection":[{"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1722"}],"version-history":[{"count":5,"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=\/wp\/v2\/posts\/1722\/revisions"}],"predecessor-version":[{"id":1735,"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=\/wp\/v2\/posts\/1722\/revisions\/1735"}],"wp:attachment":[{"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1722"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1722"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/blog.ndsc.tw\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1722"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}