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[TGx]Downloaded from torrentgalaxy.to .txt |
585б |
0 |
146б |
1 |
1.68Кб |
10 |
105.56Кб |
10 - Why to clean the data.mp4 |
20.02Мб |
10 - Why to clean the data English.vtt |
3.52Кб |
11 |
55.27Кб |
11 - Data Quality.mp4 |
51.45Мб |
11 - Data Quality English.vtt |
9.17Кб |
12 |
484.95Кб |
12 - Check if data is valid or not.mp4 |
51.91Мб |
12 - Check if data is valid or not English.vtt |
13.52Кб |
13 |
646.37Кб |
13 - Check if data is accurate or not.mp4 |
10.82Мб |
13 - Check if data is accurate or not English.vtt |
3.29Кб |
14 |
731.01Кб |
14 - Completeness of the data.mp4 |
11.25Мб |
14 - Completeness of the data English.vtt |
3.09Кб |
15 |
734.80Кб |
15 - Consistency of the data.mp4 |
13.46Мб |
15 - Consistency of the data English.vtt |
4.06Кб |
16 |
54.48Кб |
16 - Uniformity of the data.mp4 |
25.23Мб |
16 - Uniformity of the data English.vtt |
6.67Кб |
17 |
901.80Кб |
17 - How to ensure data quality.mp4 |
26.60Мб |
17 - How to ensure data quality English.vtt |
5.96Кб |
18 |
925.90Кб |
18 - Inspect the data.mp4 |
11.22Мб |
18 - Inspect the data English.vtt |
2.41Кб |
19 |
745.37Кб |
19 - Cleaning the data.mp4 |
67.48Мб |
19 - Cleaning the data English.vtt |
14.25Кб |
1 - Introduction.mp4 |
18.65Мб |
2 |
235б |
20 |
672.32Кб |
20 - Goal of data munging.mp4 |
77.49Мб |
20 - Goal of data munging English.vtt |
7.88Кб |
21 |
826.69Кб |
21 - Understand your data.mp4 |
60.89Мб |
21 - Understand your data English.vtt |
8.51Кб |
22 |
890.97Кб |
22 - Introduction to Outliers.mp4 |
45.10Мб |
22 - Introduction to Outliers English.vtt |
8.58Кб |
23 |
774.55Кб |
23 - Finalize Data Munging.mp4 |
88.46Мб |
23 - Finalize Data Munging English.vtt |
12.98Кб |
24 |
853.80Кб |
24 - Handle data type mismatch.mp4 |
242.79Мб |
24 - Handle data type mismatch English.vtt |
27.27Кб |
24 - pandas-data-type-mismatch.ipynb |
44.75Кб |
25 |
1007.77Кб |
25 - pandas-duplicate-data.ipynb |
22.23Кб |
25 - Remove Duplicate data.mp4 |
89.94Мб |
25 - Remove Duplicate data English.vtt |
12.34Кб |
26 |
100.97Кб |
26 - Handling missing data.mp4 |
95.51Мб |
26 - Handling missing data English.vtt |
11.92Кб |
26 - pandas-missing-data.ipynb |
22.42Кб |
27 |
200.49Кб |
27 - Feature Importance.mp4 |
146.29Мб |
27 - Feature Importance English.vtt |
15.45Кб |
27 - Sklearn-Feature-Importance.ipynb |
113.25Кб |
28 |
655.87Кб |
28 - Plot feature importance plot.mp4 |
60.61Мб |
28 - Plot feature importance plot English.vtt |
6.45Кб |
28 - Sklearn-Feature-Importance.ipynb |
113.25Кб |
29 |
696.55Кб |
29 - Introduction to Feature Importance.mp4 |
55.69Мб |
29 - Introduction to Feature Importance English.vtt |
10.70Кб |
2 - Install anaconda on your machine.mp4 |
69.05Мб |
2 - Install anaconda on your machine English.vtt |
12.33Кб |
3 |
126б |
30 |
897.92Кб |
30 - Data Normalization.mp4 |
23.02Мб |
30 - Data Normalization English.vtt |
4.21Кб |
30 - min-max-scaler.ipynb |
48.52Кб |
31 |
652.19Кб |
31 - Data Standardization.mp4 |
48.30Мб |
31 - Data Standardization English.vtt |
10.76Кб |
32 |
888.13Кб |
32 - min-max-scaler.ipynb |
48.52Кб |
32 - Normalization in practice.mp4 |
125.17Мб |
32 - Normalization in practice English.vtt |
12.09Кб |
33 |
617.45Кб |
33 - Standardization in practice.mp4 |
138.10Мб |
33 - Standardization in practice English.vtt |
16.31Кб |
33 - standard-scaler.ipynb |
38.13Кб |
34 |
272.53Кб |
34 - Introduction to One Hot Encoding.mp4 |
55.78Мб |
34 - Introduction to One Hot Encoding English.vtt |
12.46Кб |
34 - one-hot-encoding.ipynb |
16.16Кб |
35 |
990.48Кб |
35 - one-hot-encoding.ipynb |
16.16Кб |
35 - One Hot Encoding in practice.mp4 |
116.90Мб |
35 - One Hot Encoding in practice English.vtt |
15.16Кб |
36 |
458.31Кб |
36 - Types of data in Machine Learning.mp4 |
31.59Мб |
36 - Types of data in Machine Learning English.vtt |
10.68Кб |
37 |
120.51Кб |
37 - Structured format for datasets.mp4 |
69.64Мб |
37 - Structured format for datasets English.vtt |
9.95Кб |
38 |
500.02Кб |
38 - Introduction to pandas library.mp4 |
164.11Мб |
38 - Introduction to pandas library English.vtt |
32.60Кб |
39 |
798.21Кб |
39 - Train Test split Concept.mp4 |
89.46Мб |
39 - Train Test split Concept English.vtt |
18.90Кб |
3 - Set up environment and Download Machine Learning Libraries.mp4 |
80.51Мб |
3 - Set up environment and Download Machine Learning Libraries English.vtt |
16.72Кб |
4 |
68.05Кб |
40 |
817.53Кб |
40 - Decision Tree part 1.mp4 |
140.12Мб |
40 - Decision Tree part 1 English.vtt |
37.18Кб |
41 |
63.57Кб |
41 - Decision Tree part 2.mp4 |
116.80Мб |
41 - Decision Tree part 2 English.vtt |
30.61Кб |
42 |
549.31Кб |
42 - Code Decision Tree classifier.mp4 |
235.47Мб |
42 - Code Decision Tree classifier English.vtt |
34.66Кб |
42 - Decision-Tree-Classifier.ipynb |
28.61Кб |
43 |
550.45Кб |
43 - Decision-Tree-Classifier.ipynb |
28.61Кб |
43 - Decision Tree GINI index.mp4 |
95.20Мб |
43 - Decision Tree GINI index English.vtt |
12.78Кб |
44 |
890.01Кб |
44 - Introduction to Linear Regression.mp4 |
156.37Мб |
44 - Introduction to Linear Regression English.vtt |
18.50Кб |
45 |
32.36Кб |
45 - Learn about OLS [Ordinary Least Squares] algorithm.mp4 |
246.81Мб |
45 - Learn about OLS [Ordinary Least Squares] algorithm English.vtt |
34.06Кб |
46 |
509.32Кб |
46 - Introduction to working of Linear Regression.mp4 |
194.56Мб |
46 - Introduction to working of Linear Regression English.vtt |
40.63Кб |
47 |
501.46Кб |
47 - Lecture Introduction to MSE, MAE, RMSE.mp4 |
56.96Мб |
47 - Lecture Introduction to MSE, MAE, RMSE English.vtt |
14.76Кб |
48 |
831.43Кб |
48 - Introduction to R squared.mp4 |
49.43Мб |
48 - Introduction to R squared English.vtt |
12.83Кб |
49 |
519.41Кб |
49 - Implement Simple Linear Regression.mp4 |
168.93Мб |
49 - Implement Simple Linear Regression English.vtt |
28.73Кб |
49 - linear-regression-guide.zip |
86.69Кб |
4 - Introduction to Jupyter Notebook.mp4 |
111.36Мб |
4 - Introduction to Jupyter Notebook English.vtt |
27.03Кб |
5 |
227.13Кб |
50 |
371.31Кб |
50 - Learn about Logistic Regression.mp4 |
38.33Мб |
50 - Learn about Logistic Regression English.vtt |
7.33Кб |
51 |
730.71Кб |
51 - Learn about Gradient Descent.mp4 |
45.32Мб |
51 - Learn about Gradient Descent English.vtt |
7.46Кб |
52 |
967.77Кб |
52 - Implement Logistic Regression part 1.mp4 |
145.28Мб |
52 - Implement Logistic Regression part 1 English.vtt |
25.33Кб |
52 - logistic.zip |
143.29Кб |
53 |
765.60Кб |
53 - Implement Logistic Regression part 2.mp4 |
200.69Мб |
53 - Implement Logistic Regression part 2 English.vtt |
38.79Кб |
53 - logistic.zip |
143.29Кб |
54 |
531.57Кб |
54 - Introduction to data and data dictionary.mp4 |
31.23Мб |
54 - Introduction to data and data dictionary English.vtt |
2.85Кб |
54 - Project-1.zip |
2.26Мб |
55 |
102.01Кб |
55 - Project-1.zip |
2.26Мб |
55 - Setup project and import libraries.mp4 |
14.45Мб |
55 - Setup project and import libraries English.vtt |
3.21Кб |
56 |
569.96Кб |
56 - Import data to the project.mp4 |
17.56Мб |
56 - Import data to the project English.vtt |
2.55Кб |
57 |
115.86Кб |
57 - Clean NA values.mp4 |
98.55Мб |
57 - Clean NA values English.vtt |
10.59Кб |
58 |
401.35Кб |
58 - Clean your data.mp4 |
116.32Мб |
58 - Clean your data English.vtt |
14.54Кб |
59 |
39.36Кб |
59 - Analysis 1 Where do the guest come from.mp4 |
95.22Мб |
59 - Analysis 1 Where do the guest come from English.vtt |
14.15Кб |
5 - Data Science Methodologies.mp4 |
51.21Мб |
5 - Data Science Methodologies English.vtt |
9.29Кб |
6 |
313.58Кб |
60 |
221.01Кб |
60 - Analysis 2 How much do guests pay for room per night.mp4 |
112.12Мб |
60 - Analysis 2 How much do guests pay for room per night English.vtt |
14.77Кб |
61 |
318.01Кб |
61 - Analysis 3 How does the price vary.mp4 |
134.34Мб |
61 - Analysis 3 How does the price vary English.vtt |
18.97Кб |
62 |
510.81Кб |
62 - Sorting.mp4 |
97.88Мб |
62 - Sorting English.vtt |
14.86Кб |
63 |
95.44Кб |
63 - Analysis 4 Which months are busy months.mp4 |
108.13Мб |
63 - Analysis 4 Which months are busy months English.vtt |
15.88Кб |
64 |
564.93Кб |
64 - Analysis 5 How long do people stay at the hotels.mp4 |
132.19Мб |
64 - Analysis 5 How long do people stay at the hotels English.vtt |
19.37Кб |
65 |
805.00Кб |
65 - Feature selection using coorelation.mp4 |
127.24Мб |
65 - Feature selection using coorelation English.vtt |
16.01Кб |
66 |
586.20Кб |
66 - Refine Numerical attributes.mp4 |
68.25Мб |
66 - Refine Numerical attributes English.vtt |
8.67Кб |
67 |
721.80Кб |
67 - Refine Categorical attributes.mp4 |
99.03Мб |
67 - Refine Categorical attributes English.vtt |
10.82Кб |
68 |
691.64Кб |
68 - Augment the data.mp4 |
63.90Мб |
68 - Augment the data English.vtt |
8.86Кб |
69 |
917.75Кб |
69 - Mean Encoding for Categorical attributes.mp4 |
206.78Мб |
69 - Mean Encoding for Categorical attributes English.vtt |
26.37Кб |
6 - CRISP-DM model.mp4 |
42.86Мб |
6 - CRISP English.vtt |
6.90Кб |
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447.29Кб |
70 |
725.48Кб |
70 - Preparing our data.mp4 |
102.73Мб |
70 - Preparing our data English.vtt |
16.09Кб |
71 |
145.13Кб |
71 - Feature Importance.mp4 |
137.27Мб |
71 - Feature Importance English.vtt |
16.43Кб |
72 |
281.66Кб |
72 - Splitting data and Building models.mp4 |
187.62Мб |
72 - Splitting data and Building models English.vtt |
26.99Кб |
73 |
685.32Кб |
73 - Loading the data to the project.mp4 |
117.02Мб |
73 - Loading the data to the project English.vtt |
12.84Кб |
73 - Project-2.zip |
853.81Кб |
74 |
169.79Кб |
74 - Introduction to Corpus and Term Document Matrix.mp4 |
44.29Мб |
74 - Introduction to Corpus and Term Document Matrix English.vtt |
7.73Кб |
74 - Project-2.zip |
853.81Кб |
75 |
926.83Кб |
75 - Storing data into the data frame.mp4 |
78.19Мб |
75 - Storing data into the data frame English.vtt |
8.50Кб |
76 |
415.90Кб |
76 - Cleaning the data.mp4 |
245.43Мб |
77 |
786.42Кб |
77 - Creating Document Term Matrix English.vtt |
8.92Кб |
78 |
411.28Кб |
78 - Analyzing most commonly spoken words.mp4 |
141.95Мб |
78 - Analyzing most commonly spoken words English.vtt |
15.08Кб |
79 |
425.32Кб |
79 - Creating wordcloud.mp4 |
207.30Мб |
79 - Creating wordcloud English.vtt |
22.98Кб |
7 - Phases of CRISP-DM.mp4 |
26.58Мб |
7 - Phases of CRISP English.vtt |
4.36Кб |
8 |
391.65Кб |
80 |
791.59Кб |
80 - Profanity.mp4 |
81.50Мб |
80 - Profanity English.vtt |
12.76Кб |
81 |
869.32Кб |
81 - Sentimental Analysis.mp4 |
37.83Мб |
81 - Sentimental Analysis English.vtt |
5.95Кб |
82 |
1002.40Кб |
82 - Sentiment Label.mp4 |
69.29Мб |
82 - Sentiment Label English.vtt |
8.10Кб |
83 |
1005.21Кб |
83 - Plotting Polarity and Subjectivity.mp4 |
53.50Мб |
83 - Plotting Polarity and Subjectivity English.vtt |
8.25Кб |
84 |
356.17Кб |
84 - Topic Modeling.mp4 |
128.13Мб |
84 - Topic Modeling English.vtt |
14.46Кб |
85 |
455.34Кб |
85 - Topic Modeling Part Of Speech Tagging.mp4 |
104.40Мб |
85 - Topic Modeling Part Of Speech Tagging English.vtt |
12.69Кб |
86 |
567.41Кб |
86 - Text Generation.mp4 |
36.09Мб |
86 - Text Generation English.vtt |
6.00Кб |
87 |
562.72Кб |
87 - Text Generation Part 2.mp4 |
86.13Мб |
88 |
555.11Кб |
88 - Introduction to Neural Networks.mp4 |
24.15Мб |
88 - Introduction to Neural Networks English.vtt |
3.22Кб |
89 |
771.30Кб |
89 - Neuron.mp4 |
116.36Мб |
89 - Neuron English.vtt |
29.36Кб |
8 - Phases of CRISP-DM part 2.mp4 |
17.45Мб |
8 - Phases of CRISP English.vtt |
3.33Кб |
9 |
75.58Кб |
90 |
798.67Кб |
90 - Learn to create MLP model.mp4 |
156.53Мб |
90 - Learn to create MLP model English.vtt |
20.10Кб |
91 |
187.67Кб |
91 - Multi English.vtt |
24.43Кб |
91 - Multi-Layer Perception Algorithm part 2.mp4 |
166.06Мб |
92 |
753.19Кб |
92 - Multi English.vtt |
8.79Кб |
92 - Multi-Layer Perception Algorithm part 3.mp4 |
61.44Мб |
93 - Multi English.vtt |
13.29Кб |
93 - Multi-Layer Perception Algorithm part 4.mp4 |
85.97Мб |
9 - Phases of CRISP-DM part 3.mp4 |
39.72Мб |
9 - Phases of CRISP English.vtt |
7.57Кб |
TutsNode.com.txt |
63б |