AutoEncoder

ChileWang0228 · ChileWang0228 · commit 5fc774421a98 · 2019-07-27T21:57:12.000+08:00
diff --git a/AutoEncoder/.ipynb_checkpoints/AutoEncoder-checkpoint.ipynb b/AutoEncoder/.ipynb_checkpoints/AutoEncoder-checkpoint.ipynb
@@ -91,7 +91,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "  ### np.prod是将矩阵里面的数值相乘，相当于用一个数值去表示一张图片，方便BP神经元读取。"
+    "### np.prod是将28X28矩阵转化成1X784，方便BP神经网络输入层784个神经元读取。"
    ]
   },
   {
@@ -1066,7 +1066,7 @@
     "# 4.正则自编码器  \n",
     "两种类型：  \n",
     "1.稀疏正则自编码器  \n",
-    "2.加噪正则自编码器"
+    "2.去噪正则自编码器"
    ]
   },
   {
@@ -1115,7 +1115,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### np.prod是将矩阵里面的数值相乘，相当于用一个数值去表示一张图片，方便BP神经元读取。"
+    "### np.prod是将28X28矩阵转化成1X784，方便BP神经网络输入层784个神经元读取。"
    ]
   },
   {
@@ -1373,7 +1373,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 2.加噪自编码器"
+    "## 2.去噪自编码器"
    ]
   },
   {
@@ -1423,7 +1423,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 加噪自编码器建模"
+    "## 去噪自编码器建模"
    ]
   },
   {
diff --git a/AutoEncoder/AutoEncoder.ipynb b/AutoEncoder/AutoEncoder.ipynb
@@ -1066,7 +1066,7 @@
     "# 4.正则自编码器  \n",
     "两种类型：  \n",
     "1.稀疏正则自编码器  \n",
-    "2.加噪正则自编码器"
+    "2.去噪正则自编码器"
    ]
   },
   {
@@ -1373,7 +1373,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 2.加噪自编码器"
+    "## 2.去噪自编码器"
    ]
   },
   {
@@ -1423,7 +1423,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 加噪自编码器建模"
+    "## 去噪自编码器建模"
    ]
   },
   {

Original file line number	Diff line number	Diff line change
`@@ -91,7 +91,7 @@`
`91`	`91`	`"cell_type": "markdown",`
`92`	`92`	`"metadata": {},`
`93`	`93`	`"source": [`
`94`		`- " ### np.prod是将矩阵里面的数值相乘，相当于用一个数值去表示一张图片，方便BP神经元读取。"`
	`94`	`+ "### np.prod是将28X28矩阵转化成1X784，方便BP神经网络输入层784个神经元读取。"`
`95`	`95`	`]`
`96`	`96`	`},`
`97`	`97`	`{`
`@@ -1066,7 +1066,7 @@`
`1066`	`1066`	`"# 4.正则自编码器 \n",`
`1067`	`1067`	`"两种类型： \n",`
`1068`	`1068`	`"1.稀疏正则自编码器 \n",`
`1069`		`- "2.加噪正则自编码器"`
	`1069`	`+ "2.去噪正则自编码器"`
`1070`	`1070`	`]`
`1071`	`1071`	`},`
`1072`	`1072`	`{`
`@@ -1115,7 +1115,7 @@`
`1115`	`1115`	`"cell_type": "markdown",`
`1116`	`1116`	`"metadata": {},`
`1117`	`1117`	`"source": [`
`1118`		`- "### np.prod是将矩阵里面的数值相乘，相当于用一个数值去表示一张图片，方便BP神经元读取。"`
	`1118`	`+ "### np.prod是将28X28矩阵转化成1X784，方便BP神经网络输入层784个神经元读取。"`
`1119`	`1119`	`]`
`1120`	`1120`	`},`
`1121`	`1121`	`{`
`@@ -1373,7 +1373,7 @@`
`1373`	`1373`	`"cell_type": "markdown",`
`1374`	`1374`	`"metadata": {},`
`1375`	`1375`	`"source": [`
`1376`		`- "## 2.加噪自编码器"`
	`1376`	`+ "## 2.去噪自编码器"`
`1377`	`1377`	`]`
`1378`	`1378`	`},`
`1379`	`1379`	`{`
`@@ -1423,7 +1423,7 @@`
`1423`	`1423`	`"cell_type": "markdown",`
`1424`	`1424`	`"metadata": {},`
`1425`	`1425`	`"source": [`
`1426`		`- "## 加噪自编码器建模"`
	`1426`	`+ "## 去噪自编码器建模"`
`1427`	`1427`	`]`
`1428`	`1428`	`},`
`1429`	`1429`	`{`