RAR-files |
ilearn-nlprwpip.rar |
50,000,000 |
775B001F |
ilearn-nlprwpip.r00 |
50,000,000 |
2538A3A7 |
ilearn-nlprwpip.r01 |
50,000,000 |
71A04B99 |
ilearn-nlprwpip.r02 |
50,000,000 |
73A1643A |
ilearn-nlprwpip.r03 |
50,000,000 |
F6618FA4 |
ilearn-nlprwpip.r04 |
50,000,000 |
911D3BDE |
ilearn-nlprwpip.r05 |
50,000,000 |
DA8F7B29 |
ilearn-nlprwpip.r06 |
50,000,000 |
53658E6C |
ilearn-nlprwpip.r07 |
50,000,000 |
06FBFB72 |
ilearn-nlprwpip.r08 |
50,000,000 |
AE339027 |
ilearn-nlprwpip.r09 |
50,000,000 |
122CC38C |
ilearn-nlprwpip.r10 |
50,000,000 |
779C7B14 |
ilearn-nlprwpip.r11 |
50,000,000 |
9924F684 |
ilearn-nlprwpip.r12 |
50,000,000 |
AABDEACB |
ilearn-nlprwpip.r13 |
50,000,000 |
FE398A12 |
ilearn-nlprwpip.r14 |
50,000,000 |
9EE17B88 |
ilearn-nlprwpip.r15 |
50,000,000 |
68F19888 |
ilearn-nlprwpip.r16 |
50,000,000 |
5F7B8EFD |
ilearn-nlprwpip.r17 |
50,000,000 |
02F86CB7 |
ilearn-nlprwpip.r18 |
50,000,000 |
06513D2E |
ilearn-nlprwpip.r19 |
50,000,000 |
B99A493D |
ilearn-nlprwpip.r20 |
50,000,000 |
9F525762 |
ilearn-nlprwpip.r21 |
50,000,000 |
B99C2A71 |
ilearn-nlprwpip.r22 |
50,000,000 |
3A4DE01F |
ilearn-nlprwpip.r23 |
50,000,000 |
334E60DB |
ilearn-nlprwpip.r24 |
50,000,000 |
E9823705 |
ilearn-nlprwpip.r25 |
50,000,000 |
5CE6D9E1 |
ilearn-nlprwpip.r26 |
50,000,000 |
6AF34BF4 |
ilearn-nlprwpip.r27 |
50,000,000 |
DD841401 |
ilearn-nlprwpip.r28 |
50,000,000 |
BA95B1DA |
ilearn-nlprwpip.r29 |
50,000,000 |
4E318C60 |
ilearn-nlprwpip.r30 |
50,000,000 |
0B9B095C |
ilearn-nlprwpip.r31 |
50,000,000 |
7B38D06E |
ilearn-nlprwpip.r32 |
50,000,000 |
D96B505D |
ilearn-nlprwpip.r33 |
50,000,000 |
F672E07F |
ilearn-nlprwpip.r34 |
50,000,000 |
ACD8AA83 |
ilearn-nlprwpip.r35 |
50,000,000 |
99169C08 |
ilearn-nlprwpip.r36 |
50,000,000 |
F0B315B9 |
ilearn-nlprwpip.r37 |
38,539,360 |
9E811E06 |
|
Total size: |
1,938,539,360 |
|
|
Archived
files |
4. Introduction to Business Problem & Dataset.mp4
[dc098918d6e11226]
|
24,881,911 |
B51C29D7 |
6. Perform Data Pre-processing on Amazon Data.mp4
[e6ed231be1e3031f]
|
63,093,017 |
207C6846 |
7. Apply Exploratory Data Analysis on Data.mp4
[4b967cf4d160a3e5]
|
54,468,078 |
8A71D53D |
8. Intuition behind Bag of Words.mp4
[c5dff0b8efd20e2b]
|
65,647,312 |
EFDE057B |
9. Intuition behind Logistic Regression --part 1.mp4
[1a844f295ab485a9]
|
60,781,373 |
F49E2691 |
10. Intuition behind Logistic Regression --part 2.mp4
[463fcfbb168c564e]
|
46,292,725 |
9B6A7CAB |
11. Apply Bag of Words on data.mp4
[3ee83ed49db8a864]
|
100,615,681 |
30C61234 |
12. Automate your NLP model & Machine Learning Model.mp4
[b334792496d2251d]
|
112,285,412 |
1893894F |
13. Intuition behind TF-IDF --part 1.mp4
[5e0a96d081f34068]
|
25,986,228 |
89754F13 |
14. Intuition behind TF-IDF --part 2.mp4
[c8ad934c282b39e6]
|
36,269,209 |
07150A8F |
15. Applying algorithms of NLP & Machine Learning.mp4
[41ef0ed40ba5dfb0]
|
61,608,196 |
D4938E4A |
16. Data Preparation for Modelling Purpose.mp4
[70e80e60fd97ab4c]
|
58,291,676 |
9BF39DAB |
17. What is Imbalance Data & how to handle it.mp4
[63a00d050f678e36]
|
89,699,135 |
16DA5146 |
18. Part1-- What is Cross-validation & when to use it.mp4
[38199a6848fe2f01]
|
43,687,861 |
306916DA |
19. Part2-- What is Cross-validation & when to use it.mp4
[5c028116907fa8c1]
|
70,605,982 |
1FB78A60 |
20. Applying Techniques of Handling Imbalance Data & Cross Validation.mp4
[12c565c09ed8b800]
|
104,164,835 |
D5C0D509 |
21. Introduction to Business Problem & Dataset.mp4
[3d22f4baf07c52ce]
|
24,928,708 |
A99791C9 |
23. Data Pre-processing on Data..mp4
[7156db6978749d70]
|
88,122,916 |
9AC93550 |
24. Perfrom Data Wrangling & Merging.mp4
[20d424cd056caf57]
|
75,528,920 |
5E1B5A28 |
25. Intuition Behind Random Forest Part-1.mp4
[e82b9c70b92eba2b]
|
81,535,998 |
9414C477 |
26. Intuition behind Random Forest --part 2.mp4
[66c51c34f8a9aa82]
|
53,255,133 |
BEBEA886 |
27. Apply Bag of words and Random forest on Data.mp4
[d09dcb3305816221]
|
65,273,293 |
48679769 |
28. Model Evaluation...mp4
[248efead941880f2]
|
52,467,666 |
11804BB1 |
29. Intuition Behind Naive Bayes-Part 1.mp4
[a4c1171d442f197d]
|
72,374,837 |
8EA850EF |
30. Intuition Behind Naive Bayes- Part 2.mp4
[5927b2e6cb877d3]
|
97,122,192 |
F634FC3C |
31. Apply Naive Bayes on Data...mp4
[1e94a386a2fb0ba3]
|
38,615,551 |
C71C2281 |
32. Introduction to Business Problem & Dataset.mp4
[b7aceac727314f5]
|
14,363,063 |
9D1050F5 |
34. Exploring Data.mp4
[f7f0bb8f7b1c730f]
|
59,832,497 |
356E03F0 |
35. Apply TF-IDF on data.mp4
[36582feaf2f49e91]
|
63,490,857 |
060E344B |
36. Apply Logistic Regression on Data.mp4
[1a965f34fc32799]
|
55,529,808 |
C8141013 |
37. Checking Accuracy of Model.mp4
[3feac5ae152b1e52]
|
29,572,754 |
9F2A1951 |
1. Intro To course.mp4
[b8806055f1b103dd]
|
20,279,427 |
00A912F1 |
2. Utilize this GOLDEN oppurtunity , QnA section !!.mp4
[70a1520f7ca74581]
|
9,831,922 |
B27ECD48 |
3. How to follow this course-Must Watch.mp4
[ea30d52c7e396b71]
|
18,027,768 |
9C50FEB8 |
|
Total size: |
1,938,531,941 |
|
|