|
RAR-files |
| ilearn-upbfdsaml.rar |
350,000,000 |
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| ilearn-upbfdsaml.r00 |
350,000,000 |
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| ilearn-upbfdsaml.r07 |
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| ilearn-upbfdsaml.r08 |
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| ilearn-upbfdsaml.r09 |
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| ilearn-upbfdsaml.r10 |
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| ilearn-upbfdsaml.r12 |
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| ilearn-upbfdsaml.r13 |
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| ilearn-upbfdsaml.r14 |
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| Total size: |
6,809,647,789 |
|
|
| Archived
files |
|
16. Theory On Data Indexing And Selection.mp4
[e3fd6c350ceca6e5]
|
39,417,084 |
60FA4C48 |
|
17. Data Selection In Series Part 1.mp4
[650c66790dc7a63]
|
31,859,686 |
05C7C9B2 |
|
18. Data Selection In Series Part 2.mp4
[dbe49adadcc5eca9]
|
13,033,789 |
D7C4F982 |
|
19. Indexers Loc And Iloc In Series.mp4
[43f5fb961f616e0e]
|
78,697,680 |
D92D1DCF |
|
20. Data Selection In DataFrame Part 1.mp4
[ca3157de02404ae8]
|
37,750,384 |
2F52E72F |
|
21. Data Selection In DataFrame Part 2.mp4
[afce2cc397c22835]
|
25,504,423 |
68174914 |
|
22. Accessing Values Using Loc Iloc And Ix In DataFrame Objects.mp4
[20279011d8cc4f1c]
|
69,552,979 |
9AB7085C |
|
23. Practice Part 02.mp4
[4c34a92fc345fc94]
|
20,139,457 |
E798C283 |
|
24. Practice Part 02 Solution.mp4
[b4adeecb15cb2a5d]
|
100,086,815 |
26982E93 |
|
25. Theory On Essential Functionalities.mp4
[952f1a042e198b6e]
|
63,623,463 |
197BBC73 |
|
26. How To Reindex Pandas Objects.mp4
[b3f99e8344938b5]
|
81,129,901 |
CDB8451D |
|
27. How To Drop Entries From An Axis.mp4
[3e6b6dc83b2f165f]
|
53,080,646 |
98D2C2F4 |
|
28. Arithmetic And Data Alignment.mp4
[d60c1f8f864d79c8]
|
46,503,776 |
D3D75E06 |
|
29. Arithmetic Methods With Fill Values.mp4
[1c8cefab0f24379c]
|
95,645,029 |
310391BD |
|
30. Broadcasting In Pandas.mp4
[3e4f3af22d622fa8]
|
40,967,478 |
408D93C0 |
|
31. Apply And Applymap In Pandas.mp4
[c5a294dcbc122dcc]
|
54,409,781 |
DCA52FA2 |
|
32. How To Sort And Rank In Pandas.mp4
[edb29093f93f5980]
|
96,710,880 |
9E191251 |
|
33. How To Work With The Duplicated Indices.mp4
[929a1317352405dd]
|
26,527,419 |
0F9C0384 |
|
34. Summarising And Computing Descriptive Statistics.mp4
[6d17edbbe02929e7]
|
43,342,001 |
C1511A9E |
|
35. Unique Values Value Counts And Membership.mp4
[9484fa443126348d]
|
74,817,994 |
04A778C1 |
|
36. Practice_Part_03.mp4
[a4293c5a9876134e]
|
17,544,623 |
07DC48C2 |
|
37. Practice_Part_03 Solution.mp4
[4b2ebec54133a52f]
|
133,230,607 |
5AB6798E |
|
38. Theory On Data Handling.mp4
[fea86377a37a50b1]
|
31,402,080 |
7AC46238 |
|
39. How To Read The Csv Files Part - 1.mp4
[7b128db9435a6ad8]
|
150,990,377 |
0EBFAADF |
|
40. How To Read The Csv Files Part - 2.mp4
[aa3e936a52ae56d7]
|
114,411,364 |
786B0009 |
|
41. How To Read Text Files In Pieces.mp4
[fb407bbf4f1252a3]
|
61,328,908 |
68C8E8EE |
|
42. How To Export Data In Text Format.mp4
[689bcee6767dcc2b]
|
77,132,860 |
E1DCB591 |
|
43. How To Use Python's Csv Module.mp4
[3731463c09897cae]
|
65,763,417 |
1CB354B7 |
|
44. Practice_Part_04.mp4
[322515d31fc0df07]
|
21,208,586 |
4D333DAB |
|
45. Practice_Part_04 Solution.mp4
[45ccad90ee53e974]
|
135,019,708 |
269A5493 |
|
46. Theory On Data Preprocessing.mp4
[add5969941a57e36]
|
79,333,483 |
1BCCDEF9 |
|
47. How To Handle Missing Values.mp4
[4e7f9cab59d11539]
|
58,416,900 |
BAF484AA |
|
48. How To Filter The Missing Values.mp4
[b9fbdd9108d89a5d]
|
57,084,292 |
1C3380B5 |
|
49. How To Filter The Missing Values Part 2.mp4
[4a2e238cf02447c0]
|
61,383,531 |
04A3F04B |
|
50. How To Remove Duplicate Rows And Values.mp4
[7465c718d65e949]
|
73,739,688 |
5EF26586 |
|
51. How To Replace The Non Null Values.mp4
[81397d2723ef203e]
|
55,924,574 |
BFEEC415 |
|
52. How To Rename The Axis Labels.mp4
[52b133d551d0c4ee]
|
42,746,554 |
C2923249 |
|
53. How To Descretize And Bin The Data Part - 1.mp4
[dc379ba1bb96f77a]
|
165,564,721 |
3AFB1D1B |
|
54. How To Filter And Detect The Outliers.mp4
[9a28e3c6304605e4]
|
25,630,936 |
CA646BFF |
|
55. How To Reorder And Select Randomly.mp4
[52237276cc3d7e69]
|
38,436,896 |
CFA4A1D4 |
|
56. Converting The Categorical Variables Into Dummy Variables.mp4
[b434c194a0c340c4]
|
65,013,419 |
32E0EF95 |
|
57. How To Use 'map' Method.mp4
[4d0cdf3305de1e43]
|
47,587,058 |
ACADEB79 |
|
58. How To Manipulate With Strings.mp4
[5ea3a4cc82bcb3d8]
|
78,900,094 |
E171A54C |
|
59. Using Regular Expressions.mp4
[5b43c89fd334e95]
|
135,598,873 |
72EA263C |
|
60. Working With The Vectorized String Functions.mp4
[1219eec72d19c178]
|
55,059,224 |
FF8654F2 |
|
61. Practice_Part_05.mp4
[b847f46789597593]
|
20,358,576 |
9E6B57A1 |
|
62. Practice_Part_05 Solution.mp4
[427f725d4fee2ecb]
|
144,616,605 |
4F34C6F9 |
|
63. Theory On Data Wrangling.mp4
[b7e9eb6c5438dab1]
|
56,808,158 |
FDA5BF5B |
|
64. Hierarchical Indexing.mp4
[56646965002024ba]
|
47,856,054 |
A2D1954D |
|
65. Hierarchical Indexing Reordering And Sorting.mp4
[7d2b065f0c1debf3]
|
40,748,308 |
25EFA84E |
|
66. Summary Statistics By Level.mp4
[a7ffe3a6f9c60b90]
|
19,145,275 |
1BAE6A75 |
|
67. Hierarchical Indexing With DataFrame Columns.mp4
[5c5dd2c0c659514a]
|
30,435,864 |
10F980D0 |
|
68. How To Merge The Pandas Objects.mp4
[6af6e786fe390f7]
|
145,184,987 |
D43871E2 |
|
69. Merging On Row Index.mp4
[905733907d111a7b]
|
93,209,454 |
235D4E1D |
|
70. How To Concatenate Along An Axis.mp4
[c5f40304a40ee64b]
|
132,119,337 |
BEC7348E |
|
71. How To Combine With Overlap.mp4
[499f0c3f6bdbbe0e]
|
39,298,244 |
AB9F15BA |
|
72. How To Reshape And Pivot Data In Pandas.mp4
[251088507c5011a7]
|
59,523,041 |
CF26D21D |
|
73. Practice_Part_06.mp4
[6e39adc0a8a976ef]
|
8,821,784 |
8CADF0FB |
|
74. Practice_Part_06 Solution.mp4
[162e9233bfa19d5b]
|
57,308,127 |
911669F7 |
|
75. Thoery On Data Groupby And Aggregation.mp4
[69ba3bd7497880d3]
|
26,609,182 |
6CFBF060 |
|
76. Groupby Operation.mp4
[f2981fb6fe86250d]
|
107,277,215 |
76211B6C |
|
77. How To Iterate Over Groupby Object.mp4
[70d09bc5c03eecda]
|
37,406,122 |
1FEF9FD1 |
|
78. How To Select Columns In Groupby Method.mp4
[2bb760ae34f9568]
|
17,997,919 |
3DD89273 |
|
79. Grouping Using Dictionaries And Series.mp4
[b8c0ec029d2e3f2d]
|
19,524,433 |
7BE6691D |
|
80. Grouping Using Functions And Index Level.mp4
[7fbaeb04f8a213b8]
|
39,564,789 |
9818469F |
|
81. Data Aggregation.mp4
[fd4598301cb1994c]
|
78,330,372 |
B30A3C24 |
|
82. Practice_Part_07.mp4
[2b33f67040a3f13b]
|
24,713,910 |
669B41BF |
|
83. Practice_Part_07 Solution.mp4
[8844ea6f8d2e6319]
|
108,524,392 |
42669775 |
|
84. Theory On Time Series Analysis.mp4
[bb05012fc256f2b0]
|
47,308,756 |
FF6F1590 |
|
85. Introduction To Time Series Data Types.mp4
[91449a9c70a8ad1f]
|
62,748,837 |
918F694F |
|
86. How To Convert Between String And Datetime.mp4
[3266e1120c687240]
|
99,611,553 |
BF8C90CD |
|
87. Time Series Basics With Pandas Objects.mp4
[cd695cb9e8ae7bd0]
|
89,290,797 |
A1A28C0B |
|
88. Date Ranges Frequencies And Shifting.mp4
[6eaae7e566d4a2ee]
|
92,974,309 |
457DB45A |
|
89. Date Ranges Frequencies And Shifting Part - 2.mp4
[eeddca297fb31ea5]
|
77,541,515 |
1567CB91 |
|
90. Time Zone Handling.mp4
[23c9b95252aa4de3]
|
63,232,359 |
14727937 |
|
91. Periods And Period Arithmetic’s.mp4
[b4bb52b413620e64]
|
69,361,675 |
59642D23 |
|
92. Practice_Part_08.mp4
[194bf89db80e418d]
|
21,668,056 |
16F9AB6C |
|
93. Practice_Part_08 Solution.mp4
[a14e944ef521d90d]
|
111,696,935 |
4862F391 |
|
94. A Brief Introduction To The Pandas Projects.mp4
[c7dc549d6753ba41]
|
51,370,788 |
394B74C9 |
|
95. Project_1 Description.mp4
[85f89fbe80ef4a7b]
|
45,398,257 |
DC5AC67F |
|
96. Project_1 Solution Part - 1.mp4
[3104dbf201784c5f]
|
167,532,146 |
4A19B443 |
|
97. Project_1 Solution Part - 2.mp4
[c80e293b7d8021c0]
|
129,391,493 |
2FA5ECE4 |
|
98. Project_2 Description.mp4
[e576c6cf084b3022]
|
17,413,744 |
F6989D6D |
|
99. Project_2 Solution.mp4
[48b536b3ddecc321]
|
185,843,827 |
50664369 |
|
100. Project_3 Description.mp4
[e9f563aff1a34a6]
|
19,343,301 |
EB9832FA |
|
101. Project_3 Solution Part - 1.mp4
[2767fc54452eafa4]
|
112,933,039 |
0912BF2C |
|
102. Project_3 Solution Part - 2.mp4
[441198dc87899e41]
|
126,917,144 |
7B363B64 |
|
1. Course Introduction.mp4
[d9fc32898ae790c7]
|
28,584,997 |
3BF7C63D |
|
2. How To Get Most Out Of This Course.mp4
[b38cbbf11fdadb97]
|
8,492,866 |
5FC836A7 |
|
3. Better To Know These Things.mp4
[78b05005c71b173]
|
17,557,360 |
29445FD4 |
|
4. How To Install Python IPython And Jupyter Notebook.mp4
[a40b9a85ed87016a]
|
64,968,896 |
68C08C00 |
|
5. How To Install Anaconda For macOS And Linux Users.mp4
[d84349d47dba9590]
|
74,140,805 |
E186DC9C |
|
6. How To Work With The Jupyter Notebook Part-1.mp4
[eb6b37cab027d70c]
|
81,783,744 |
B81FDA7F |
|
7. How To Work With The Jupyter Notebook Part-2.mp4
[d96a69a04567284c]
|
69,728,876 |
8CA4C724 |
|
8. How To Work With The Tabular Data.mp4
[48b24b4bca5df614]
|
23,419,425 |
CF919F9E |
|
9. How To Read The Documentation In Pandas.mp4
[a3301f92295675d1]
|
98,409,672 |
653CCA3D |
|
10. Theory On Pandas Data Structures.mp4
[9da32b79d713eda7]
|
32,874,360 |
A02F0587 |
|
11. How To Construct The Pandas Series.mp4
[adb6371e4f31c7ab]
|
64,547,806 |
36FBCB2B |
|
12. How To Construct The DataFrame Objects.mp4
[ff3562cbc5b79996]
|
74,873,875 |
15C52374 |
|
13. How To Construct The Pandas Index Objects.mp4
[fa08a6fbd4573755]
|
79,337,661 |
5F44EBAA |
|
14. Practice Part 01.mp4
[fd8ba72d432f6ef9]
|
29,248,315 |
60FE7CE0 |
|
15. Practice Part 01 Solution.mp4
[e939b15ac1921a77]
|
173,455,007 |
E68857F8 |
|
| Total size: |
6,809,637,782 |
|
|
