diff --git a/5_nn/3-softmax_ce.ipynb b/5_nn/3-softmax_ce.ipynb index fe99c61..76a294e 100644 --- a/5_nn/3-softmax_ce.ipynb +++ b/5_nn/3-softmax_ce.ipynb @@ -263,6 +263,7 @@ "## 参考资料\n", "\n", "* [一文详解Softmax函数](https://zhuanlan.zhihu.com/p/105722023)\n", + "* [损失函数:交叉熵详解](https://zhuanlan.zhihu.com/p/115277553)\n", "* [交叉熵代价函数(作用及公式推导)](https://blog.csdn.net/u014313009/article/details/51043064)\n", "* [手打例子一步一步带你看懂softmax函数以及相关求导过程](https://www.jianshu.com/p/ffa51250ba2e)\n", "* [简单易懂的softmax交叉熵损失函数求导](https://www.jianshu.com/p/c02a1fbffad6)" diff --git a/6_pytorch/1-tensor.ipynb b/6_pytorch/1-tensor.ipynb index 896558a..d52c4f3 100644 --- a/6_pytorch/1-tensor.ipynb +++ b/6_pytorch/1-tensor.ipynb @@ -42,7 +42,9 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "import torch\n", @@ -52,7 +54,9 @@ { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 创建一个 numpy ndarray\n", @@ -69,7 +73,9 @@ { "cell_type": "code", "execution_count": 9, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "pytorch_tensor1 = torch.tensor(numpy_tensor)\n", @@ -100,7 +106,9 @@ { "cell_type": "code", "execution_count": 5, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 如果 pytorch tensor 在 cpu 上\n", @@ -129,7 +137,9 @@ { "cell_type": "code", "execution_count": 7, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 第一种方式是定义 cuda 数据类型\n", @@ -160,7 +170,9 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "cpu_tensor = gpu_tensor.cpu()" @@ -716,7 +728,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.9" + "version": "3.5.4" } }, "nbformat": 4, diff --git a/6_pytorch/2-autograd.ipynb b/6_pytorch/2-autograd.ipynb index 644bd57..c93f799 100644 --- a/6_pytorch/2-autograd.ipynb +++ b/6_pytorch/2-autograd.ipynb @@ -119,7 +119,9 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "z = torch.mean(torch.matmul(w, x) + b) # torch.matmul 是做矩阵乘法\n", @@ -275,7 +277,9 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "n.backward(torch.ones_like(n)) # 将 (w0, w1) 取成 (1, 1)" @@ -349,7 +353,9 @@ { "cell_type": "code", "execution_count": 18, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "y.backward(retain_graph=True) # 设置 retain_graph 为 True 来保留计算图" @@ -375,7 +381,9 @@ { "cell_type": "code", "execution_count": 20, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "y.backward() # 再做一次自动求导,这次不保留计算图" @@ -455,7 +463,9 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "x = torch.tensor([2, 3], dtype=torch.float, requires_grad=True)\n", @@ -553,7 +563,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -567,7 +577,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.5.4" } }, "nbformat": 4, diff --git a/6_pytorch/3-linear-regression.ipynb b/6_pytorch/3-linear-regression.ipynb index 2db4de0..c1ad752 100644 --- a/6_pytorch/3-linear-regression.ipynb +++ b/6_pytorch/3-linear-regression.ipynb @@ -151,7 +151,9 @@ { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 转换成 Tensor\n", @@ -166,7 +168,9 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 构建线性回归模型\n", @@ -180,7 +184,9 @@ { "cell_type": "code", "execution_count": 5, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "y_ = linear_model(x_train)" @@ -275,7 +281,9 @@ { "cell_type": "code", "execution_count": 8, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 自动求导\n", @@ -305,7 +313,9 @@ { "cell_type": "code", "execution_count": 10, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 更新一次参数\n", @@ -542,7 +552,9 @@ { "cell_type": "code", "execution_count": 17, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 构建数据 x 和 y\n", @@ -582,7 +594,9 @@ { "cell_type": "code", "execution_count": 19, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 定义参数\n", @@ -670,7 +684,9 @@ { "cell_type": "code", "execution_count": 22, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 自动求导\n", @@ -702,7 +718,9 @@ { "cell_type": "code", "execution_count": 24, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "# 更新一下参数\n", @@ -853,7 +871,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -867,7 +885,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.5.4" } }, "nbformat": 4, diff --git a/6_pytorch/optimizer/6_6-adam.ipynb b/6_pytorch/optimizer/6_6-adam.ipynb index 48ff972..15cb6df 100644 --- a/6_pytorch/optimizer/6_6-adam.ipynb +++ b/6_pytorch/optimizer/6_6-adam.ipynb @@ -47,7 +47,9 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "def adam(parameters, vs, sqrs, lr, t, beta1=0.9, beta2=0.999):\n", @@ -63,7 +65,9 @@ { "cell_type": "code", "execution_count": 2, - "metadata": {}, + "metadata": { + "collapsed": true + }, "outputs": [], "source": [ "import numpy as np\n", @@ -267,7 +271,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -281,7 +285,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.5.4" } }, "nbformat": 4, diff --git a/7_deep_learning/1_CNN/2-vgg.ipynb b/7_deep_learning/1_CNN/2-vgg.ipynb index e0db203..b21bfde 100644 --- a/7_deep_learning/1_CNN/2-vgg.ipynb +++ b/7_deep_learning/1_CNN/2-vgg.ipynb @@ -462,7 +462,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.9" + "version": "3.5.4" } }, "nbformat": 4, diff --git a/7_deep_learning/1_CNN/CNN_Introduction.pptx b/7_deep_learning/1_CNN/CNN_Introduction.pptx index 843c650..52e5bcc 100644 Binary files a/7_deep_learning/1_CNN/CNN_Introduction.pptx and b/7_deep_learning/1_CNN/CNN_Introduction.pptx differ