深度学习与PyTorch入门实战教程

1. P01 Lesson01 PyTorch介绍.mp448.66MB
2. P02 Lesson02 开发环境准备.mp454.47MB
3. P03 Lesson03 初探Linear Regression案例-1.mp471.93MB
4. P04 Lesson03 初探Linear Regression案例-2.mp443.15MB
5. P05 Lesson04 PyTorch求解Linear Regression案例.mp435.72MB
6. P06 Lesson05 手写数字问题引入-1.mp436.74MB
7. P07 Lesson05 手写数字问题引入-2.mp421.03MB
8. P08 Lesson06 基本数据类型-1.mp454.35MB
9. P09 Lesson06 基本数据类型-2.mp428.2MB
10. P10 Lesson07 创建Tensor-1.mp451.58MB
11. P11 Lesson07 创建Tensor-2.mp444.27MB
12. P12 Lesson08 索引与切片-1.mp447.24MB
13. P13 Lesson08 索引与切片-2.mp445.42MB
14. P14 Lesson09 Tensor维度变换-1.mp433.07MB
15. P15 Lesson09 Tensor维度变换-2.mp440.69MB
16. P16 Lesson09 Tensor维度变换-3.mp440.76MB
17. P17 Lesson09 Tensor维度变换-4.mp440.8MB
18. P18 Lesson10 Broadcasting自动扩展-1.mp457.86MB
19. P19 Lesson10 Broadcasting自动扩展-2.mp446.18MB
20. P20 Lesson11 拼接与拆分-1.mp446.78MB
21. P21 Lesson11 拼接与拆分-2.mp430.81MB
22. P22 Lesson12 基本运算.mp467.11MB
23. P23 Lesson13 统计属性-1.mp439.94MB
24. P24 Lesson13 统计属性-2.mp454.7MB
25. P25 Lesson14 高阶OP.mp461.86MB
26. P26 Lesson16 什么是梯度-1.mp469.17MB
27. P27 Lesson16 什么是梯度-2.mp443.31MB
28. P28 Lesson17 常见函数梯度.mp418.38MB
29. P29 Lesson18 激活函数及其梯度-1.mp445.53MB
30. P30 Lesson18 激活函数及其梯度-2.mp444.38MB
31. P31 Lesson18 激活函数及其梯度-3.mp465.34MB
32. P32 Lesson19 感知机-1.mp447.44MB
33. P33 Lesson19 感知机-2.mp449.69MB
34. P34 Lesson20 链式法则.mp439.94MB
35. P35 Lesson21 MLP反向传播.mp482.01MB
36. P36 Lesson22 2D函数优化实例.mp439.18MB
37. P37 Lesson24 Logistic Regression.mp447.84MB
38. P38 Lesson25 交叉熵.mp472.77MB
39. P39 Lesson26 多分类问题.mp435MB
40. P40 Lesson27 全连接层.mp452.13MB
41. P41 Lesson28 激活函数与GPU加速.mp439.59MB
42. P42 Lesson29 测试.mp453.8MB
43. P43 Lesson30 Visdom可视化.mp452.77MB
44. P44 Lesson31 过拟合与欠拟合.mp442.48MB
45. P45 Lesson32 Train-Val-Test划分-1.mp445.95MB
46. P46 Lesson32 Train-Val-Test划分-2.mp432.32MB
47. P47 Lesson33 Regularization.mp439.04MB
48. P48 Lesson34 动量与学习率衰减.mp451.46MB
49. P49 Lesson35 Early Stop, Dropout.mp451.23MB
50. P50 Lesson37 什么是卷积-1.mp462.76MB
51. P51 Lesson37 什么是卷积-2.mp439.6MB
52. P52 Lesson38 卷积神经网络-1.mp441.36MB
53. P53 Lesson38 卷积神经网络-2.mp462.89MB
54. P54 Lesson38 卷积神经网络-3.mp435.46MB
55. P55 Lesson39 Down sample, up sample.mp434.05MB
56. P56 Lesson40 Batch Norm-1.mp441.45MB
57. P57 Lesson40 Batch Norm-2.mp451.27MB
58. P58 Lesson41 经典卷积网络-1.mp449.28MB
59. P59 Lesson41 经典卷积网络-2.mp440.38MB
60. P60 Lesson42 深度残差网络-1.mp453.18MB
61. P61 Lesson42 深度残差网络-2.mp443.56MB
62. P62 Lesson43 nn.Module-1.mp444.98MB
63. P63 Lesson43 nn.Module-2.mp431.43MB
64. P64 Lesson44 数据增强.mp446.85MB
65. P65 Lesson46 时间序列表示.mp453.55MB
66. P66 Lesson47 循环神经网络-1.mp428.41MB
67. P67 Lesson47 循环神经网络-2.mp434.94MB
68. P68 Lesson48 RNN Layer使用-1.mp434.23MB
69. P69 Lesson48 RNN Layer使用-2.mp429.91MB
70. P70 Lesson49 时间序列预测.mp453.3MB
71. P71 Lesson50 RNN训练难题.mp455MB
72. P72 Lesson51 LSTM-1.mp432.97MB
73. P73 Lesson51 LSTM-2.mp445.7MB
74. P74 Lesson52 LSTM使用.mp428.45MB
75. P75 Lesson53 情感分类实战.mp468.58MB