RAR-files |
booktime-psdfsium.rar |
50,000,000 |
5A6928C7 |
booktime-psdfsium.r00 |
50,000,000 |
F2D6BC54 |
booktime-psdfsium.r01 |
50,000,000 |
88FE2D15 |
booktime-psdfsium.r02 |
50,000,000 |
D83E278B |
booktime-psdfsium.r03 |
50,000,000 |
109856CF |
booktime-psdfsium.r04 |
50,000,000 |
F5C59F28 |
booktime-psdfsium.r05 |
50,000,000 |
DFA8BC13 |
booktime-psdfsium.r06 |
50,000,000 |
1F93B7D0 |
booktime-psdfsium.r07 |
50,000,000 |
519D884A |
booktime-psdfsium.r08 |
50,000,000 |
097F55D8 |
booktime-psdfsium.r09 |
50,000,000 |
9EF10E4D |
booktime-psdfsium.r10 |
50,000,000 |
DC7CACD7 |
booktime-psdfsium.r11 |
50,000,000 |
48395DBE |
booktime-psdfsium.r12 |
50,000,000 |
D7784F9A |
booktime-psdfsium.r13 |
50,000,000 |
19F3B91E |
booktime-psdfsium.r14 |
50,000,000 |
2F17F6FF |
booktime-psdfsium.r15 |
50,000,000 |
EC81CED8 |
booktime-psdfsium.r16 |
50,000,000 |
41A90EB4 |
booktime-psdfsium.r17 |
50,000,000 |
B437052B |
booktime-psdfsium.r18 |
50,000,000 |
523BD869 |
booktime-psdfsium.r19 |
50,000,000 |
DB2F98F0 |
booktime-psdfsium.r20 |
50,000,000 |
FDED053A |
booktime-psdfsium.r21 |
50,000,000 |
C4AFE7D5 |
booktime-psdfsium.r22 |
50,000,000 |
BFA6C3C4 |
booktime-psdfsium.r23 |
50,000,000 |
CF6B7EDB |
booktime-psdfsium.r24 |
17,979,897 |
8BE38BA2 |
|
Total size: |
1,267,979,897 |
|
|
Archived
files |
Chapter_2-Run_Length_Encoding_and_Decoding\10. Explore the RLE encodings for our Dataset.mp4
[6075a1f8b51011c6]
|
71,984,826 |
FB294D3F |
Chapter_2-Run_Length_Encoding_and_Decoding\11. Create a segmented mask from RLE encodings.mp4
[d80df893f5138a93]
|
117,405,746 |
FD687AC4 |
Chapter_2-Run_Length_Encoding_and_Decoding\12. Create a Function that can convert given RLE encodings to Mask.mp4
[a2418fdb5fca1f7a]
|
32,716,237 |
6CCD3A59 |
Chapter_2-Run_Length_Encoding_and_Decoding\13. Module Outro.mp4
[31683f7a49df246f]
|
7,187,981 |
F085B28C |
Chapter_2-Run_Length_Encoding_and_Decoding\8. Module Intro.mp4
[9aa4b0a2a3010f48]
|
7,031,812 |
7E586972 |
Chapter_2-Run_Length_Encoding_and_Decoding\9. Run Length Encoding and Decoding.mp4
[bfc821322c7709ed]
|
79,504,912 |
E3543402 |
Chapter_3-Data_Preparation_and_Preprocessing\14. Module Intro.mp4
[7967a08ff2aecb5a]
|
3,966,607 |
27264DDB |
Chapter_3-Data_Preparation_and_Preprocessing\15. Initiating Train and Validation Data Preparation.mp4
[c9e44751a233883c]
|
81,543,477 |
7BBD0B72 |
Chapter_3-Data_Preparation_and_Preprocessing\16. Random Undersampling for Ships in the Dataset.mp4
[30bde54ca57882b5]
|
59,450,457 |
E7ED90A4 |
Chapter_3-Data_Preparation_and_Preprocessing\17. Setting up Parameters for Model Building and Training.mp4
[9a323cea4d32cc2b]
|
22,934,764 |
58042305 |
Chapter_3-Data_Preparation_and_Preprocessing\18. Build the Training and Validation Dataset.mp4
[9e04b752f52c8d7b]
|
132,348,222 |
7E974A5F |
Chapter_3-Data_Preparation_and_Preprocessing\19. Data Augmentation for Images and Masks.mp4
[95120011e75b3af]
|
62,309,718 |
78E6C4EA |
Chapter_3-Data_Preparation_and_Preprocessing\20. Garbage Collection.mp4
[94093b4ef3a617c2]
|
19,965,240 |
88D31E6D |
Chapter_3-Data_Preparation_and_Preprocessing\21. Module Outro.mp4
[d14448d68dea9409]
|
4,063,674 |
B0E50A51 |
Chapter_4-Image_Segmentation_using_UNET\22. Module Intro.mp4
[f83c924aa39365c4]
|
6,030,546 |
DB097AC3 |
Chapter_4-Image_Segmentation_using_UNET\23. Overall Idea of UNET and CNNs.mp4
[cf6d2f75a5064cc5]
|
16,958,511 |
6E9C905B |
Chapter_4-Image_Segmentation_using_UNET\24. Convolutions and Pooling Layers in CNN.mp4
[829eb872438af712]
|
32,606,914 |
CE4F717F |
Chapter_4-Image_Segmentation_using_UNET\25. But why UNET and these layers.mp4
[ed13a28d776d6454]
|
22,632,796 |
A5D5DF01 |
Chapter_4-Image_Segmentation_using_UNET\26. Understand and Build UNET.mp4
[fdbca8c5f33a3f9]
|
166,522,163 |
A34A0067 |
Chapter_4-Image_Segmentation_using_UNET\27. Compile the Model (combo loss solution).mp4
[3c1c38c1dff52682]
|
51,730,374 |
C865A015 |
Chapter_4-Image_Segmentation_using_UNET\28. Prepare Callbacks.mp4
[9e4f043303e8f59c]
|
19,288,058 |
72E96302 |
Chapter_4-Image_Segmentation_using_UNET\29. Model Training and Saving weights.mp4
[a15afa98120a30a1]
|
25,706,028 |
B137ACAA |
Chapter_4-Image_Segmentation_using_UNET\30. Module Outro.mp4
[407a2b393c021ecb]
|
4,669,888 |
022F21BE |
Chapter_4-Image_Segmentation_using_UNET\31. Project Conclusion.mp4
[45385dfce3af059b]
|
24,161,994 |
6E02729F |
Chapter_1-Project_Introduction_and_Data_Exploration\1. Introduction.mp4
[8bc84047852a1e1d]
|
8,011,316 |
9A9751F6 |
Chapter_1-Project_Introduction_and_Data_Exploration\2. Module Intro.mp4
[3fdf35ac6c1acce2]
|
5,419,135 |
165CC008 |
Chapter_1-Project_Introduction_and_Data_Exploration\3. Dataset and Aim of the Project.mp4
[7d091ff020e84086]
|
17,148,443 |
75937E33 |
Chapter_1-Project_Introduction_and_Data_Exploration\4. Some Applications of Machine Learning in Computer Vision.mp4
[17ba57a6f2a513ca]
|
37,671,121 |
80266E5E |
Chapter_1-Project_Introduction_and_Data_Exploration\5. Importing Libraries for the Project.mp4
[f0995cc58d7a7a1c]
|
27,076,206 |
80CBB5B4 |
Chapter_1-Project_Introduction_and_Data_Exploration\6. Exploring the Dataset.mp4
[16460ac83c771adf]
|
85,442,704 |
E7E5DFD3 |
Chapter_1-Project_Introduction_and_Data_Exploration\7. Module Outro.mp4
[e2da420b9a2c40be]
|
4,124,613 |
A727A4C2 |
Chapter_1-Project_Introduction_and_Data_Exploration\Additional_Files\sdsi-notebook.ipynb |
10,357,070 |
6740D911 |
Chapter_1-Project_Introduction_and_Data_Exploration\Additional_Files |
0 |
00000000 |
Chapter_2-Run_Length_Encoding_and_Decoding |
0 |
00000000 |
Chapter_3-Data_Preparation_and_Preprocessing |
0 |
00000000 |
Chapter_4-Image_Segmentation_using_UNET |
0 |
00000000 |
Chapter_1-Project_Introduction_and_Data_Exploration |
0 |
00000000 |
|
Total size: |
1,267,971,553 |
|
|