|
RAR-files |
| e-lbfnd.rar |
15,000,000 |
D667BC6B |
| e-lbfnd.r00 |
15,000,000 |
F19051FE |
| e-lbfnd.r01 |
15,000,000 |
3FC0A0C0 |
| e-lbfnd.r02 |
15,000,000 |
E5C70968 |
| e-lbfnd.r03 |
15,000,000 |
F6441AA0 |
| e-lbfnd.r04 |
15,000,000 |
2C95B624 |
| e-lbfnd.r05 |
15,000,000 |
90AB958A |
| e-lbfnd.r06 |
15,000,000 |
2CDDD576 |
| e-lbfnd.r07 |
15,000,000 |
4EA4D481 |
| e-lbfnd.r08 |
15,000,000 |
D5C402CD |
| e-lbfnd.r09 |
505,733 |
355260E2 |
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| Total size: |
150,505,733 |
|
|
| Archived
files |
|
01 - Course_Overview.mp4 |
4,003,530 |
6225059C |
|
10 - Demo_-_Standardize_Data_Using_the_Scale_Function.mp4 |
8,812,591 |
3E88DBC9 |
|
12 - Robust_Scaler.mp4 |
4,823,474 |
2A6A625F |
|
04 - Scaling_and_Standardization.mp4 |
5,104,424 |
72D58917 |
|
11 - Demo_-_Standardize_Data_Using_the_Standard_Scalar_Estimator_and_Apply_Bessels_Correction.mp4 |
6,629,810 |
90A6CE3D |
|
14 - Summary.mp4 |
1,843,197 |
DED06C9E |
|
09 - Standard_Scaler.mp4 |
5,290,358 |
443A9074 |
|
06 - Understanding_Variance.mp4 |
4,988,256 |
4AC044FB |
|
08 - Demo_-_Box_Plot_Visualization_and_Data_Standardization.mp4 |
10,559,774 |
F44CF4C6 |
|
05 - Mean_Variance_and_Standard_Deviation.mp4 |
4,755,221 |
EFA8D837 |
|
07 - Demo_-_Calculating_Mean_Variance_and_Standard_Deviation.mp4 |
12,529,971 |
F4D5BA54 |
|
02 - Module_Overview.mp4 |
1,303,220 |
488497C0 |
|
13 - Demo_-_Scaling_Data_Using_the_Robust_Scaler.mp4 |
11,824,211 |
E136043F |
|
03 - Prerequisites_and_Course_Outline.mp4 |
2,535,007 |
5FDC09E3 |
|
22 - Demo_-_Normalization_Using_L1_L2_and_Max_Norms.mp4 |
8,791,274 |
A6DD1294 |
|
15 - Module_Overview.mp4 |
1,013,405 |
A2A5C793 |
|
16 - What_Is_Normalization.mp4 |
2,045,450 |
5F80B6D3 |
|
21 - L1_L2_and_Max_Norms.mp4 |
2,804,734 |
7DF85EC9 |
|
17 - Normalization_and_Cosine_Similarity.mp4 |
10,623,802 |
A39034DF |
|
20 - Demo_-_K-means_Clustering_with_Cosine_Similarity.mp4 |
9,714,987 |
178D2728 |
|
23 - Summary.mp4 |
1,382,678 |
96FEDE3F |
|
19 - Demo_-_Normalizing_Data_to_Simplify_Cosine_Similarity_Calculations.mp4 |
7,846,597 |
9C3DE69E |
|
18 - Demo_-_Cosine_Similarity_and_the_L2_Norm.mp4 |
11,982,092 |
02295A3E |
|
41 - Summary_and_Further_Study.mp4 |
2,638,209 |
0FACDF47 |
|
30 - Demo_-_Scaling_with_the_MaxAbsScaler.mp4 |
3,407,140 |
1FA612D1 |
|
25 - Converting_Continuous_Data_to_Categorical.mp4 |
3,356,982 |
34859DEE |
|
36 - Transforming_Features_to_Gaussian-like_Distributions_Using_Power_Transformers.mp4 |
1,839,823 |
83A74EE4 |
|
27 - Demo_-_Using_the_KBinsDiscretizer_to_Categorize_Numeric_Values.mp4 |
9,072,404 |
A8E829F5 |
|
31 - Demo_-_Scaling_with_the_MinMaxScaler.mp4 |
5,008,124 |
EDA5D4FA |
|
37 - Demo_-_Working_with_Chi_Squared_Distributed_Input_Features.mp4 |
8,653,925 |
C65C1904 |
|
29 - Scaling_Data.mp4 |
1,867,132 |
3B978CBE |
|
33 - Demo_-_Performing_Custom_Transforms_Using_the_FunctionTransformer.mp4 |
4,814,267 |
4EE6D61E |
|
28 - Demo_-_Using_Bin_Values_to_Flag_Outliers.mp4 |
5,024,598 |
29BB99B4 |
|
24 - Module_Overview.mp4 |
1,582,694 |
C2572484 |
|
38 - Demo_-_Applying_Power_Transformers_to_Get_Normal_Distributions.mp4 |
7,381,557 |
F5D0428D |
|
39 - Transforming_Data_to_Normal_or_Uniform_Distributions_Using_Quantile_Transformers.mp4 |
1,363,654 |
39FFBE90 |
|
32 - Custom_Transformations.mp4 |
670,274 |
11638E3C |
|
26 - Demo_-_Convert_Numeric_Data_to_Binary_Categories_Using_a_Binarizer.mp4 |
8,524,937 |
210BE1E0 |
|
40 - Demo_-_Tranforming_to_a_Normal_Distribution_Using_the_QuantileTransformer.mp4 |
6,619,474 |
E785E2B4 |
|
35 - Demo_-_Using_Polynomial_Features_to_Transform_Data.mp4 |
10,701,969 |
0BA30359 |
|
34 - Generating_Polynomial_Features.mp4 |
2,733,623 |
781FF91F |
|
building-features-numeric-data.zip |
2,340,772 |
715C58A6 |
|
| Total size: |
228,809,621 |
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|
