搜索
[FreeCourseSite.com] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks
磁力链接/BT种子名称
[FreeCourseSite.com] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks
磁力链接/BT种子简介
种子哈希:
8ebe89a440306d6d38c1851617ec5b6de82b798d
文件大小:
4.76G
已经下载:
460
次
下载速度:
极快
收录时间:
2021-03-11
最近下载:
2024-12-08
移花宫入口
移花宫.com
邀月.com
怜星.com
花无缺.com
yhgbt.icu
yhgbt.top
磁力链接下载
magnet:?xt=urn:btih:8EBE89A440306D6D38C1851617EC5B6DE82B798D
推荐使用
PIKPAK网盘
下载资源,10TB超大空间,不限制资源,无限次数离线下载,视频在线观看
下载BT种子文件
磁力链接
迅雷下载
PIKPAK在线播放
91视频
含羞草
欲漫涩
逼哩逼哩
成人快手
51品茶
抖阴破解版
暗网禁地
91短视频
TikTok成人版
PornHub
草榴社区
乱伦社区
最近搜索
anime lilith
有点肥
各种大屁股应接不暇
momomo小学生
我要舔原味
superprodukcja lem
蜜桃视频
black angel
萝莉
超级肛交
小仙女合集
媚娘
台湾白虎b少妇
我是刑警
摄像头
人前是你妈+人后任你插+广州越秀区高考母子
abaodz
gremlins 1990 1080p
美人奥
舅妈
itim rinrada
一念永恒txt
tbw
museum
偷偷自慰
妹妹apk
city-feet
被小哥哥无套猛怼
dandy931
麻王
文件列表
7. Building a CNN/1.1 Section 40 - Convolutional Neural Networks (CNN).zip
234.9 MB
7. Building a CNN/8. Building a CNN - FINAL DEMO!.mp4
160.2 MB
25. Logistic Regression Implementation/8. Logistic Regression - Step 7.mp4
124.4 MB
7. Building a CNN/4. Building a CNN - Step 3.mp4
124.4 MB
4. Building an ANN/5. Building an ANN - Step 2.mp4
116.4 MB
7. Building a CNN/3. Building a CNN - Step 2.mp4
112.1 MB
24. Data Preprocessing Template/8. Data Preprocessing - Step 7.mp4
106.7 MB
4. Building an ANN/8. Building an ANN - Step 5.mp4
106.2 MB
7. Building a CNN/6. Building a CNN - Step 5.mp4
102.5 MB
24. Data Preprocessing Template/6. Data Preprocessing - Step 5.mp4
93.0 MB
25. Logistic Regression Implementation/3. Logistic Regression - Step 2.mp4
88.8 MB
4. Building an ANN/6. Building an ANN - Step 3.mp4
78.7 MB
24. Data Preprocessing Template/4. Data Preprocessing - Step 3.srt
75.3 MB
24. Data Preprocessing Template/4. Data Preprocessing - Step 3.mp4
75.3 MB
7. Building a CNN/2. Building a CNN - Step 1.mp4
74.2 MB
24. Data Preprocessing Template/5. Data Preprocessing - Step 4.mp4
72.4 MB
24. Data Preprocessing Template/7. Data Preprocessing - Step 6.mp4
70.9 MB
4. Building an ANN/3. Building an ANN - Step 1.mp4
69.7 MB
4. Building an ANN/7. Building an ANN - Step 4.mp4
68.5 MB
18. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.mp4
67.7 MB
13. SOMs Intuition/8. Reading an Advanced SOM.mp4
64.9 MB
18. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.mp4
61.4 MB
24. Data Preprocessing Template/2. Data Preprocessing - Step 1.mp4
57.0 MB
18. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.mp4
56.7 MB
25. Logistic Regression Implementation/7. Logistic Regression - Step 6.mp4
55.6 MB
9. RNN Intuition/6. Practical intuition.mp4
55.4 MB
21. Building an AutoEncoder/17. THANK YOU bonus video.mp4
54.8 MB
21. Building an AutoEncoder/11. Building an AutoEncoder - Step 6.mp4
54.7 MB
6. CNN Intuition/8. Step 4 - Full Connection.srt
53.4 MB
21. Building an AutoEncoder/9. Building an AutoEncoder - Step 4.mp4
52.0 MB
15. Mega Case Study/4. Mega Case Study - Step 3.mp4
51.6 MB
9. RNN Intuition/5. LSTMs.mp4
48.2 MB
25. Logistic Regression Implementation/5. Logistic Regression - Step 4.mp4
47.4 MB
25. Logistic Regression Implementation/2. Logistic Regression - Step 1.mp4
46.8 MB
25. Logistic Regression Implementation/4. Logistic Regression - Step 3.mp4
45.2 MB
6. CNN Intuition/8. Step 4 - Full Connection.mp4
44.8 MB
18. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.srt
43.6 MB
18. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.mp4
43.6 MB
6. CNN Intuition/6. Step 2 - Pooling.mp4
42.2 MB
7. Building a CNN/5. Building a CNN - Step 4.mp4
42.0 MB
10. Building a RNN/14. Building a RNN - Step 13.mp4
41.8 MB
18. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.mp4
41.3 MB
17. Boltzmann Machine Intuition/4. Restricted Boltzmann Machine.mp4
41.2 MB
9. RNN Intuition/3. The idea behind Recurrent Neural Networks.mp4
39.1 MB
10. Building a RNN/5. Building a RNN - Step 4.mp4
38.9 MB
21. Building an AutoEncoder/5. Building an AutoEncoder - Step 1.mp4
38.5 MB
14. Building a SOM/5. Building a SOM - Step 3.mp4
37.8 MB
18. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.mp4
35.7 MB
21. Building an AutoEncoder/13. Building an AutoEncoder - Step 8.mp4
35.5 MB
21. Building an AutoEncoder/12. Building an AutoEncoder - Step 7.mp4
35.3 MB
6. CNN Intuition/10. Softmax & Cross-Entropy.mp4
34.9 MB
18. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.mp4
34.8 MB
17. Boltzmann Machine Intuition/1. Boltzmann Machine.mp4
33.5 MB
21. Building an AutoEncoder/14. Building an AutoEncoder - Step 9.mp4
33.1 MB
1. Welcome to the course/1. What is Deep Learning.mp4
32.8 MB
18. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.mp4
32.7 MB
13. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).mp4
32.6 MB
6. CNN Intuition/4. Step 1 - Convolution Operation.mp4
32.5 MB
15. Mega Case Study/5. Mega Case Study - Step 4.mp4
32.4 MB
14. Building a SOM/3. Building a SOM - Step 1.mp4
32.2 MB
25. Logistic Regression Implementation/6. Logistic Regression - Step 5.mp4
32.0 MB
18. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.mp4
31.9 MB
18. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.mp4
31.0 MB
3. ANN Intuition/3. The Neuron.mp4
31.0 MB
17. Boltzmann Machine Intuition/5. Contrastive Divergence.mp4
31.0 MB
6. CNN Intuition/3. What are convolutional neural networks.mp4
30.9 MB
10. Building a RNN/12. Building a RNN - Step 11.mp4
30.7 MB
23. Regression & Classification Intuition/5. Logistic Regression Intuition.mp4
30.6 MB
9. RNN Intuition/4. The Vanishing Gradient Problem.mp4
30.4 MB
14. Building a SOM/6. Building a SOM - Step 4.mp4
30.1 MB
21. Building an AutoEncoder/16. Building an AutoEncoder - Step 11.mp4
29.7 MB
20. AutoEncoders Intuition/1. Auto Encoders.mp4
29.6 MB
21. Building an AutoEncoder/6. Building an AutoEncoder - Step 2.mp4
29.2 MB
17. Boltzmann Machine Intuition/3. Editing Wikipedia - Our Contribution to the World.mp4
28.7 MB
3. ANN Intuition/6. How do Neural Networks learn.mp4
27.8 MB
10. Building a RNN/6. Building a RNN - Step 5.mp4
27.5 MB
18. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.mp4
27.2 MB
18. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.mp4
26.4 MB
13. SOMs Intuition/4. K-Means Clustering (Refresher).mp4
26.2 MB
3. ANN Intuition/5. How do Neural Networks work.mp4
24.7 MB
18. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.mp4
23.5 MB
13. SOMs Intuition/10. EXTRA K-means Clustering (part 3).mp4
22.9 MB
10. Building a RNN/16. Building a RNN - Step 15.mp4
22.7 MB
10. Building a RNN/15. Building a RNN - Step 14.mp4
22.6 MB
10. Building a RNN/8. Building a RNN - Step 7.mp4
21.8 MB
1. Welcome to the course/2. Updates on Udemy Reviews.mp4
21.4 MB
18. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.mp4
21.4 MB
21. Building an AutoEncoder/7. Building an AutoEncoder - Step 3.mp4
21.1 MB
13. SOMs Intuition/2. How do Self-Organizing Maps Work.mp4
21.0 MB
14. Building a SOM/4. Building a SOM - Step 2.mp4
20.4 MB
13. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).mp4
19.6 MB
13. SOMs Intuition/7. Live SOM example.mp4
19.4 MB
3. ANN Intuition/7. Gradient Descent.mp4
19.4 MB
17. Boltzmann Machine Intuition/2. Energy-Based Models (EBM).mp4
19.4 MB
3. ANN Intuition/8. Stochastic Gradient Descent.mp4
17.6 MB
4. Building an ANN/1. Business Problem Description.mp4
17.2 MB
24. Data Preprocessing Template/3. Data Preprocessing - Step 2.mp4
16.7 MB
10. Building a RNN/4. Building a RNN - Step 3.mp4
16.7 MB
10. Building a RNN/3. Building a RNN - Step 2.mp4
16.3 MB
18. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.mp4
16.2 MB
3. ANN Intuition/4. The Activation Function.mp4
15.5 MB
6. CNN Intuition/5. Step 1(b) - ReLU Layer.mp4
14.8 MB
20. AutoEncoders Intuition/5. Sparse Autoencoders.srt
14.7 MB
20. AutoEncoders Intuition/5. Sparse Autoencoders.mp4
14.7 MB
10. Building a RNN/2. Building a RNN - Step 1.mp4
14.4 MB
20. AutoEncoders Intuition/3. Training an Auto Encoder.mp4
14.2 MB
10. Building a RNN/13. Building a RNN - Step 12.mp4
14.1 MB
10. Building a RNN/9. Building a RNN - Step 8.mp4
14.1 MB
15. Mega Case Study/3. Mega Case Study - Step 2.mp4
14.0 MB
17. Boltzmann Machine Intuition/6. Deep Belief Networks.mp4
13.2 MB
13. SOMs Intuition/9. EXTRA K-means Clustering (part 2).mp4
13.0 MB
21. Building an AutoEncoder/10. Building an AutoEncoder - Step 5.mp4
12.4 MB
10. Building a RNN/11. Building a RNN - Step 10.mp4
12.0 MB
21. Building an AutoEncoder/15. Building an AutoEncoder - Step 10.mp4
11.8 MB
3. ANN Intuition/9. Backpropagation.mp4
11.5 MB
23. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.mp4
9.9 MB
10. Building a RNN/10. Building a RNN - Step 9.mp4
8.6 MB
6. CNN Intuition/9. Summary.mp4
8.3 MB
20. AutoEncoders Intuition/4. Overcomplete hidden layers.mp4
8.0 MB
9. RNN Intuition/7. EXTRA LSTM Variations.mp4
7.7 MB
10. Building a RNN/7. Building a RNN - Step 6.mp4
7.1 MB
14. Building a SOM/2. How to get the dataset.mp4
6.8 MB
17. Boltzmann Machine Intuition/8. How to get the dataset.mp4
6.8 MB
21. Building an AutoEncoder/2. How to get the dataset.mp4
6.8 MB
6. CNN Intuition/2. Plan of attack.mp4
6.2 MB
17. Boltzmann Machine Intuition/7. Deep Boltzmann Machines.mp4
6.1 MB
20. AutoEncoders Intuition/6. Denoising Autoencoders.mp4
6.0 MB
15. Mega Case Study/2. Mega Case Study - Step 1.mp4
5.7 MB
23. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.mp4
5.6 MB
20. AutoEncoders Intuition/7. Contractive Autoencoders.mp4
5.5 MB
24. Data Preprocessing Template/1.1 Machine Learning A-Z (Codes and Datasets).zip
5.5 MB
25. Logistic Regression Implementation/1.1 Machine Learning A-Z (Codes and Datasets).zip
5.5 MB
4. Building an ANN/2.1 Machine Learning A-Z (Codes and Datasets).zip
5.5 MB
13. SOMs Intuition/1. Plan of attack.mp4
5.5 MB
3. ANN Intuition/2. Plan of Attack.mp4
5.0 MB
20. AutoEncoders Intuition/8. Stacked Autoencoders.mp4
4.8 MB
9. RNN Intuition/2. Plan of attack.mp4
4.4 MB
19. ---------------------------- Part 6 - AutoEncoders ----------------------------/2. Plan of attack.mp4
4.3 MB
13. SOMs Intuition/3. Why revisit K-Means.mp4
4.3 MB
16. ------------------------- Part 5 - Boltzmann Machines -------------------------/2. Plan of attack.mp4
4.0 MB
20. AutoEncoders Intuition/9. Deep Autoencoders.mp4
3.5 MB
6. CNN Intuition/7. Step 3 - Flattening.mp4
3.4 MB
20. AutoEncoders Intuition/2. A Note on Biases.mp4
2.6 MB
23. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.mp4
1.9 MB
10. Building a RNN/1.1 Part 3 - Recurrent Neural Networks.zip
51.6 kB
18. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.srt
43.5 kB
7. Building a CNN/8. Building a CNN - FINAL DEMO!.srt
42.4 kB
21. Building an AutoEncoder/9. Building an AutoEncoder - Step 4.srt
42.1 kB
9. RNN Intuition/5. LSTMs.srt
40.3 kB
17. Boltzmann Machine Intuition/4. Restricted Boltzmann Machine.srt
38.7 kB
18. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.srt
36.8 kB
3. ANN Intuition/3. The Neuron.srt
36.6 kB
14. Building a SOM/5. Building a SOM - Step 3.srt
36.0 kB
21. Building an AutoEncoder/11. Building an AutoEncoder - Step 6.srt
35.5 kB
6. CNN Intuition/10. Softmax & Cross-Entropy.srt
35.4 kB
18. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.srt
35.0 kB
24. Data Preprocessing Template/8. Data Preprocessing - Step 7.srt
35.0 kB
4. Building an ANN/5. Building an ANN - Step 2.srt
33.8 kB
23. Regression & Classification Intuition/5. Logistic Regression Intuition.srt
33.4 kB
6. CNN Intuition/4. Step 1 - Convolution Operation.srt
33.0 kB
9. RNN Intuition/3. The idea behind Recurrent Neural Networks.srt
32.5 kB
21. Building an AutoEncoder/13. Building an AutoEncoder - Step 8.srt
31.9 kB
6. CNN Intuition/3. What are convolutional neural networks.srt
31.8 kB
17. Boltzmann Machine Intuition/5. Contrastive Divergence.srt
31.8 kB
10. Building a RNN/14. Building a RNN - Step 13.srt
31.7 kB
13. SOMs Intuition/4. K-Means Clustering (Refresher).srt
31.6 kB
7. Building a CNN/3. Building a CNN - Step 2.srt
31.4 kB
17. Boltzmann Machine Intuition/1. Boltzmann Machine.srt
31.0 kB
7. Building a CNN/4. Building a CNN - Step 3.srt
30.5 kB
9. RNN Intuition/4. The Vanishing Gradient Problem.srt
30.4 kB
13. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).srt
29.8 kB
13. SOMs Intuition/8. Reading an Advanced SOM.srt
29.2 kB
6. CNN Intuition/6. Step 2 - Pooling.srt
29.2 kB
9. RNN Intuition/6. Practical intuition.srt
28.6 kB
15. Mega Case Study/4. Mega Case Study - Step 3.srt
28.4 kB
21. Building an AutoEncoder/12. Building an AutoEncoder - Step 7.srt
28.3 kB
3. ANN Intuition/6. How do Neural Networks learn.srt
28.1 kB
21. Building an AutoEncoder/14. Building an AutoEncoder - Step 9.srt
27.8 kB
4. Building an ANN/8. Building an ANN - Step 5.srt
27.2 kB
3. ANN Intuition/5. How do Neural Networks work.srt
26.9 kB
14. Building a SOM/3. Building a SOM - Step 1.srt
26.9 kB
10. Building a RNN/5. Building a RNN - Step 4.srt
26.0 kB
25. Logistic Regression Implementation/8. Logistic Regression - Step 7.srt
25.7 kB
24. Data Preprocessing Template/6. Data Preprocessing - Step 5.srt
25.6 kB
13. SOMs Intuition/10. EXTRA K-means Clustering (part 3).srt
25.6 kB
25. Logistic Regression Implementation/3. Logistic Regression - Step 2.srt
25.5 kB
18. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.srt
25.3 kB
4. Building an ANN/6. Building an ANN - Step 3.srt
24.8 kB
7. Building a CNN/6. Building a CNN - Step 5.srt
24.7 kB
21. Building an AutoEncoder/6. Building an AutoEncoder - Step 2.srt
24.6 kB
21. Building an AutoEncoder/16. Building an AutoEncoder - Step 11.srt
24.5 kB
1. Welcome to the course/1. What is Deep Learning.srt
24.4 kB
24. Data Preprocessing Template/7. Data Preprocessing - Step 6.srt
23.7 kB
21. Building an AutoEncoder/5. Building an AutoEncoder - Step 1.srt
23.6 kB
18. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.srt
23.1 kB
17. Boltzmann Machine Intuition/2. Energy-Based Models (EBM).srt
22.4 kB
4. Building an ANN/7. Building an ANN - Step 4.srt
22.3 kB
20. AutoEncoders Intuition/1. Auto Encoders.srt
21.9 kB
14. Building a SOM/6. Building a SOM - Step 4.srt
21.9 kB
15. Mega Case Study/5. Mega Case Study - Step 4.srt
21.9 kB
18. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.srt
21.3 kB
18. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.srt
21.0 kB
24. Data Preprocessing Template/5. Data Preprocessing - Step 4.srt
20.8 kB
10. Building a RNN/6. Building a RNN - Step 5.srt
20.1 kB
7. Building a CNN/2. Building a CNN - Step 1.srt
20.0 kB
14. Building a SOM/4. Building a SOM - Step 2.srt
19.7 kB
3. ANN Intuition/7. Gradient Descent.srt
19.6 kB
10. Building a RNN/12. Building a RNN - Step 11.srt
19.1 kB
4. Building an ANN/3. Building an ANN - Step 1.srt
19.0 kB
18. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.srt
18.9 kB
18. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.srt
18.8 kB
13. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).srt
18.8 kB
13. SOMs Intuition/2. How do Self-Organizing Maps Work.srt
18.7 kB
24. Data Preprocessing Template/2. Data Preprocessing - Step 1.srt
18.7 kB
10. Building a RNN/16. Building a RNN - Step 15.srt
18.1 kB
3. ANN Intuition/8. Stochastic Gradient Descent.srt
18.0 kB
13. SOMs Intuition/9. EXTRA K-means Clustering (part 2).srt
17.5 kB
3. ANN Intuition/4. The Activation Function.srt
17.3 kB
25. Logistic Regression Implementation/2. Logistic Regression - Step 1.srt
17.1 kB
18. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.srt
16.8 kB
21. Building an AutoEncoder/7. Building an AutoEncoder - Step 3.srt
16.6 kB
18. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.srt
16.4 kB
25. Logistic Regression Implementation/7. Logistic Regression - Step 6.srt
16.3 kB
10. Building a RNN/8. Building a RNN - Step 7.srt
16.3 kB
10. Building a RNN/15. Building a RNN - Step 14.srt
14.5 kB
18. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.srt
13.9 kB
20. AutoEncoders Intuition/3. Training an Auto Encoder.srt
13.7 kB
25. Logistic Regression Implementation/5. Logistic Regression - Step 4.srt
13.2 kB
18. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.srt
13.1 kB
10. Building a RNN/3. Building a RNN - Step 2.srt
13.0 kB
25. Logistic Regression Implementation/4. Logistic Regression - Step 3.srt
13.0 kB
6. CNN Intuition/5. Step 1(b) - ReLU Layer.srt
12.8 kB
7. Building a CNN/5. Building a CNN - Step 4.srt
12.4 kB
10. Building a RNN/2. Building a RNN - Step 1.srt
12.3 kB
10. Building a RNN/9. Building a RNN - Step 8.srt
11.7 kB
23. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.srt
11.5 kB
25. Logistic Regression Implementation/6. Logistic Regression - Step 5.srt
11.4 kB
17. Boltzmann Machine Intuition/6. Deep Belief Networks.srt
10.8 kB
10. Building a RNN/4. Building a RNN - Step 3.srt
10.7 kB
18. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.srt
10.6 kB
4. Building an ANN/1. Business Problem Description.srt
10.6 kB
3. ANN Intuition/9. Backpropagation.srt
10.2 kB
21. Building an AutoEncoder/10. Building an AutoEncoder - Step 5.srt
10.2 kB
10. Building a RNN/13. Building a RNN - Step 12.srt
9.7 kB
10. Building a RNN/11. Building a RNN - Step 10.srt
9.6 kB
21. Building an AutoEncoder/15. Building an AutoEncoder - Step 10.srt
9.5 kB
13. SOMs Intuition/7. Live SOM example.srt
9.4 kB
15. Mega Case Study/3. Mega Case Study - Step 2.srt
9.0 kB
6. CNN Intuition/9. Summary.srt
8.7 kB
20. AutoEncoders Intuition/4. Overcomplete hidden layers.srt
8.3 kB
6. CNN Intuition/2. Plan of attack.srt
7.6 kB
9. RNN Intuition/7. EXTRA LSTM Variations.srt
6.9 kB
15. Mega Case Study/2. Mega Case Study - Step 1.srt
6.8 kB
17. Boltzmann Machine Intuition/3. Editing Wikipedia - Our Contribution to the World.srt
6.8 kB
13. SOMs Intuition/1. Plan of attack.srt
6.8 kB
10. Building a RNN/10. Building a RNN - Step 9.srt
6.7 kB
24. Data Preprocessing Template/3. Data Preprocessing - Step 2.srt
6.6 kB
17. Boltzmann Machine Intuition/7. Deep Boltzmann Machines.srt
6.4 kB
10. Building a RNN/7. Building a RNN - Step 6.srt
6.3 kB
23. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.srt
6.2 kB
3. ANN Intuition/2. Plan of Attack.srt
5.7 kB
20. AutoEncoders Intuition/6. Denoising Autoencoders.srt
5.4 kB
16. ------------------------- Part 5 - Boltzmann Machines -------------------------/2. Plan of attack.srt
5.3 kB
20. AutoEncoders Intuition/7. Contractive Autoencoders.srt
5.0 kB
9. RNN Intuition/2. Plan of attack.srt
5.0 kB
13. SOMs Intuition/3. Why revisit K-Means.srt
4.9 kB
19. ---------------------------- Part 6 - AutoEncoders ----------------------------/2. Plan of attack.srt
4.8 kB
18. Building a Boltzmann Machine/19. Evaluating the Boltzmann Machine.html
4.6 kB
1. Welcome to the course/8. Your Shortcut To Becoming A Better Data Scientist!.html
4.1 kB
20. AutoEncoders Intuition/9. Deep Autoencoders.srt
3.9 kB
6. CNN Intuition/7. Step 3 - Flattening.srt
3.9 kB
14. Building a SOM/2. How to get the dataset.srt
3.6 kB
17. Boltzmann Machine Intuition/8. How to get the dataset.srt
3.6 kB
21. Building an AutoEncoder/2. How to get the dataset.srt
3.6 kB
20. AutoEncoders Intuition/8. Stacked Autoencoders.srt
3.4 kB
26. Bonus Lectures/1. YOUR SPECIAL BONUS.html
3.1 kB
1. Welcome to the course/6. FAQBot!.html
3.1 kB
20. AutoEncoders Intuition/2. A Note on Biases.srt
2.8 kB
21. Building an AutoEncoder/17. THANK YOU bonus video.srt
2.5 kB
23. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.srt
2.2 kB
1. Welcome to the course/2. Updates on Udemy Reviews.srt
1.9 kB
10. Building a RNN/1. IMPORTANT NOTE.html
1.8 kB
11. Evaluating and Improving the RNN/1. Evaluating the RNN.html
1.8 kB
4. Building an ANN/2. IMPORTANT NOTE.html
1.7 kB
16. ------------------------- Part 5 - Boltzmann Machines -------------------------/1. Welcome to Part 5 - Boltzmann Machines.html
1.6 kB
21. Building an AutoEncoder/8. Homework Challenge - Coding Exercise.html
1.6 kB
7. Building a CNN/1. IMPORTANT NOTE.html
1.5 kB
21. Building an AutoEncoder/3. Installing PyTorch.html
1.4 kB
1. Welcome to the course/3. BONUS Learning Paths.html
1.4 kB
18. Building a Boltzmann Machine/2. Installing PyTorch.html
1.4 kB
11. Evaluating and Improving the RNN/2. Improving the RNN.html
1.3 kB
7. Building a CNN/7. Quick Note.html
1.2 kB
1. Welcome to the course/4. BONUS Meet Your Instructors.html
1.2 kB
8. ---------------------- Part 3 - Recurrent Neural Networks ----------------------/1. Welcome to Part 3 - Recurrent Neural Networks.html
1.1 kB
19. ---------------------------- Part 6 - AutoEncoders ----------------------------/1. Welcome to Part 6 - AutoEncoders.html
1.1 kB
25. Logistic Regression Implementation/1. Important Instructions.html
970 Bytes
24. Data Preprocessing Template/1. Important Instructions.html
929 Bytes
22. ------------------- Annex - Get the Machine Learning Basics -------------------/1. Annex - Get the Machine Learning Basics.html
899 Bytes
14. Building a SOM/1. IMPORTANT NOTE.html
794 Bytes
18. Building a Boltzmann Machine/1. IMPORTANT NOTE.html
681 Bytes
15. Mega Case Study/1. IMPORTANT NOTE.html
679 Bytes
21. Building an AutoEncoder/1. IMPORTANT NOTE.html
675 Bytes
23. Regression & Classification Intuition/1. What You Need for Regression & Classification.html
648 Bytes
1. Welcome to the course/5. Some Additional Resources!!.html
611 Bytes
4. Building an ANN/4. Check out our free course on ANN for Regression.html
533 Bytes
6. CNN Intuition/1. What You'll Need for CNN.html
375 Bytes
3. ANN Intuition/1. What You'll Need for ANN.html
374 Bytes
9. RNN Intuition/1. What You'll Need for RNN.html
366 Bytes
18. Building a Boltzmann Machine/4. Same Data Preprocessing in Parts 5 and 6.html
349 Bytes
21. Building an AutoEncoder/4. Same Data Preprocessing in Parts 5 and 6.html
348 Bytes
12. ------------------------ Part 4 - Self Organizing Maps ------------------------/1. Welcome to Part 4 - Self Organizing Maps.html
333 Bytes
1. Welcome to the course/7. Get the materials.html
330 Bytes
2. --------------------- Part 1 - Artificial Neural Networks ---------------------/1. Welcome to Part 1 - Artificial Neural Networks.html
309 Bytes
5. -------------------- Part 2 - Convolutional Neural Networks --------------------/1. Welcome to Part 2 - Convolutional Neural Networks.html
280 Bytes
0. Websites you may like/[FCS Forum].url
133 Bytes
0. Websites you may like/[FreeCourseSite.com].url
127 Bytes
0. Websites you may like/[CourseClub.ME].url
122 Bytes
随机展示
相关说明
本站不存储任何资源内容,只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符),并提供查询服务,是一个完全合法的搜索引擎系统。 网站不提供种子下载服务,用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责,请用户注意甄别!
>