|
RAR-files |
| ilearn-darquchop.rar |
50,000,000 |
8B4FC6C6 |
| ilearn-darquchop.r00 |
50,000,000 |
39282887 |
| ilearn-darquchop.r01 |
50,000,000 |
02076B8D |
| ilearn-darquchop.r02 |
50,000,000 |
40BE5947 |
| ilearn-darquchop.r03 |
50,000,000 |
DA804625 |
| ilearn-darquchop.r04 |
50,000,000 |
F611E952 |
| ilearn-darquchop.r05 |
50,000,000 |
10C82DC3 |
| ilearn-darquchop.r06 |
50,000,000 |
96A16B47 |
| ilearn-darquchop.r07 |
50,000,000 |
50595D85 |
| ilearn-darquchop.r08 |
50,000,000 |
01588EEF |
| ilearn-darquchop.r09 |
50,000,000 |
988707F7 |
| ilearn-darquchop.r10 |
50,000,000 |
8BB58EC4 |
| ilearn-darquchop.r11 |
50,000,000 |
3EEA93F5 |
| ilearn-darquchop.r12 |
50,000,000 |
1F78D442 |
| ilearn-darquchop.r13 |
50,000,000 |
BF99C1BF |
| ilearn-darquchop.r14 |
50,000,000 |
D4C22051 |
| ilearn-darquchop.r15 |
50,000,000 |
66C8B3A8 |
| ilearn-darquchop.r16 |
50,000,000 |
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| ilearn-darquchop.r17 |
50,000,000 |
9938C83E |
| ilearn-darquchop.r18 |
50,000,000 |
63EC9D07 |
| ilearn-darquchop.r19 |
50,000,000 |
EC705B23 |
| ilearn-darquchop.r20 |
50,000,000 |
43DBBA0B |
| ilearn-darquchop.r21 |
50,000,000 |
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| ilearn-darquchop.r22 |
50,000,000 |
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| ilearn-darquchop.r23 |
50,000,000 |
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| ilearn-darquchop.r24 |
50,000,000 |
575AED06 |
| ilearn-darquchop.r25 |
50,000,000 |
2F0E9FAB |
| ilearn-darquchop.r26 |
50,000,000 |
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| ilearn-darquchop.r27 |
50,000,000 |
2CCAA142 |
| ilearn-darquchop.r28 |
50,000,000 |
C23C5560 |
| ilearn-darquchop.r29 |
50,000,000 |
98E9CC0D |
| ilearn-darquchop.r30 |
50,000,000 |
6F5EE19C |
| ilearn-darquchop.r31 |
50,000,000 |
1EA865E9 |
| ilearn-darquchop.r32 |
50,000,000 |
174A98F1 |
| ilearn-darquchop.r33 |
50,000,000 |
3333AFC0 |
| ilearn-darquchop.r34 |
50,000,000 |
689F83C4 |
| ilearn-darquchop.r35 |
50,000,000 |
C8828807 |
| ilearn-darquchop.r36 |
50,000,000 |
59481CDB |
| ilearn-darquchop.r37 |
50,000,000 |
EE447F51 |
| ilearn-darquchop.r38 |
50,000,000 |
1AF4E3C3 |
| ilearn-darquchop.r39 |
50,000,000 |
F4A7484F |
| ilearn-darquchop.r40 |
50,000,000 |
2A7063B0 |
| ilearn-darquchop.r41 |
50,000,000 |
6997793D |
| ilearn-darquchop.r42 |
50,000,000 |
B1633A37 |
| ilearn-darquchop.r43 |
50,000,000 |
BAE948E0 |
| ilearn-darquchop.r44 |
50,000,000 |
A78421EA |
| ilearn-darquchop.r45 |
50,000,000 |
5268B304 |
| ilearn-darquchop.r46 |
50,000,000 |
661A053C |
| ilearn-darquchop.r47 |
50,000,000 |
D388E1E5 |
| ilearn-darquchop.r48 |
50,000,000 |
48B91E69 |
| ilearn-darquchop.r49 |
50,000,000 |
45829403 |
| ilearn-darquchop.r50 |
50,000,000 |
7B7725FC |
| ilearn-darquchop.r51 |
50,000,000 |
6962FA22 |
| ilearn-darquchop.r52 |
50,000,000 |
D1449B6A |
| ilearn-darquchop.r53 |
50,000,000 |
73E189CA |
| ilearn-darquchop.r54 |
50,000,000 |
BBC9B33B |
| ilearn-darquchop.r55 |
50,000,000 |
02A378D3 |
| ilearn-darquchop.r56 |
50,000,000 |
2493F7AC |
| ilearn-darquchop.r57 |
50,000,000 |
FC2E32A7 |
| ilearn-darquchop.r58 |
50,000,000 |
17AC744F |
| ilearn-darquchop.r59 |
50,000,000 |
0C457497 |
| ilearn-darquchop.r60 |
50,000,000 |
5FB845B5 |
| ilearn-darquchop.r61 |
50,000,000 |
7B95564F |
| ilearn-darquchop.r62 |
50,000,000 |
95668180 |
| ilearn-darquchop.r63 |
50,000,000 |
0F8088CE |
| ilearn-darquchop.r64 |
50,000,000 |
6614F67F |
| ilearn-darquchop.r65 |
50,000,000 |
50E266B9 |
| ilearn-darquchop.r66 |
50,000,000 |
F4A95712 |
| ilearn-darquchop.r67 |
50,000,000 |
09C54D83 |
| ilearn-darquchop.r68 |
49,838,337 |
770FAFC3 |
|
| Total size: |
3,499,838,337 |
|
|
| Archived
files |
|
5. Quick Summary of Jupyter Notebook.mp4
[57cdea746afff8c3]
|
45,497,619 |
FD885DD8 |
|
7. Lets Prepare data for Analysis.mp4
[45ce1acf1ac65cba]
|
94,766,981 |
D5825F2E |
|
8. Analysing which month have max Uber Pickups .mp4
[554d981417a5e511]
|
87,528,098 |
9BD1A412 |
|
9. Analysing In-depth analysis of Uber Trips.mp4
[c4dfcbf56cc88265]
|
105,704,596 |
BF70E757 |
|
10. Analysing Hourly Demand of Uber in New york City.mp4
[29e9815b1a896375]
|
95,979,154 |
21529165 |
|
11. Analysing most active Uber Base-number .mp4
[d9c12982ddef32d6]
|
93,086,251 |
01BA0D91 |
|
12. Lets Collect entire data.mp4
[133068ee4ccef486]
|
82,934,251 |
CB7AFC01 |
|
13. Perform Spatial Analysis to find rush of Uber Pickups.mp4
[a38706cb9e995b29]
|
74,386,144 |
6453954B |
|
14. Lets Figure out rush on various days !.mp4
[399af9b29acc9e13]
|
124,085,225 |
5E8C5DBE |
|
16. Preparing our Data for Analysis.mp4
[30da4b046dbc321e]
|
62,931,512 |
C73AD98F |
|
17. Perform Spatial Analysis on Guests Home-Town.mp4
[d240c658b422751b]
|
91,277,334 |
98495193 |
|
18. How does price of hotel vary across year.mp4
[f4d2f46b2fbf37ac]
|
111,151,695 |
F0771CBE |
|
19. Analysing Preference of Guests.mp4
[25d14f4052c5dbf1]
|
53,129,374 |
58E30346 |
|
20. Analysing relationship between special requests and cancellation..mp4
[52baa8df64ffa25]
|
55,045,702 |
0113B0A3 |
|
21. Analysing most busy month.mp4
[2fa75c728bcb49cf]
|
77,913,150 |
F242F26E |
|
22. Analysing more about Customers.mp4
[45e9f6af2eb52a2]
|
99,810,785 |
BB225DFE |
|
23. Analyse more about Data.mp4
[433f079afa9d6c7a]
|
62,473,785 |
103F9958 |
|
25. Prepare your Data for the Analysis.mp4
[de1269dc47d8774b]
|
60,028,157 |
B5CB7C52 |
|
26. Analysing Total cases, Deaths, Recovered & active cases.mp4
[84b99295f3bf758e]
|
104,305,559 |
04BC765F |
|
27. Perform EDA on Data.mp4
[6419c221652f28db]
|
89,888,251 |
9F8887AF |
|
28. Analysing those countries that gets badly affected by Corona.mp4
[3ddea23f65cac7f2]
|
117,319,880 |
835F1D4E |
|
29. Perform In-depth Analysis on Data.mp4
[3e5bf0393d652fd4]
|
148,728,904 |
989EB560 |
|
30. Automate Your Analysis.mp4
[4dd59680eadeaef4]
|
121,309,732 |
E75DBA40 |
|
32. Perfrom Descriptive Analysis on data.mp4
[225cbfad7cc152a]
|
77,176,641 |
C8F78994 |
|
33. Understanding Data & data-preprocessing.mp4
[fcf4e104bfbaa933]
|
102,993,403 |
4107A701 |
|
34. Analyse Education Status of customers.mp4
[6d4057689d4d32b8]
|
82,143,993 |
2EEBBBC7 |
|
35. Analyse Account holder distribution.mp4
[2b62f5fc0158db43]
|
61,491,262 |
4BA24D48 |
|
36. Automate your Analysis.mp4
[bc4f2179cd1fce8]
|
113,051,606 |
D8CC6AB6 |
|
37. Analyse Customers Behaviour on the basis of various attributes.mp4
[158314dddf44b415]
|
38,002,204 |
DD3665C6 |
|
38. Perform Hypothesis on Data.mp4
[ad0f2a40c01d03d0]
|
132,203,397 |
70419367 |
|
40. How to Read Data from SQLite Database..mp4
[36cf1efa1b97f2de]
|
84,639,872 |
934ABA6D |
|
41. Perform Sentiment Analysis on Data..mp4
[c21e4cc180ee2719]
|
169,067,219 |
25D1CEB9 |
|
42. How Amazon recommend product.mp4
[ae5e1d3aa4950085]
|
139,716,454 |
4C644593 |
|
43. Analyzing Feedback given by customers.mp4
[698d684090736575]
|
65,066,998 |
09278451 |
|
44. Prepare our data for Analysis.mp4
[7174e40686e2d70c]
|
146,624,096 |
880AC6A8 |
|
45. Analyzing behaviour of customers.mp4
[5962ad4f9d75cd4]
|
109,888,030 |
EEFDF328 |
|
1. Intro to this course.mp4
[fcb31c63022fabb7]
|
69,774,950 |
BEBDB8DE |
|
2. Utilize QnA of the course ( Golden Oppurtunity ) !.mp4
[4c06e04bfa05702f]
|
9,830,963 |
B4534BE7 |
|
3. How to follow this course-Must Watch.mp4
[2f4a3f38202e3acd]
|
13,975,659 |
84BC50A8 |
|
4. Installation of Anaconda Navigator.mp4
[88f2a07e0461adbe]
|
24,897,881 |
0BEB738F |
|
| Total size: |
3,499,826,767 |
|
|
