|
Please note that this page does not hosts or makes available any of the listed filenames. You
cannot download any of those files from here.
|
| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 0 |
267.00KB |
| 1 |
1.83MB |
| 1. Accessing and Making Files Available.mp4 |
34.61MB |
| 1. Adding Columns to Pandas Data Frames.mp4 |
33.58MB |
| 1. Classification vs Regression in Machine Learning.mp4 |
19.89MB |
| 1. Competitions on Kaggle Lesson 1.mp4 |
188.17MB |
| 1. Complete Data Science & Machine Learning A-Z with Python.html |
266B |
| 1. Concatenating Pandas Dataframes Concat Function.mp4 |
63.84MB |
| 1. Courses in Kaggle.mp4 |
52.14MB |
| 1. Creating a Pandas Series with a List.mp4 |
39.19MB |
| 1. Creating NumPy Array with The Array() Function.mp4 |
29.50MB |
| 1. Creating Pandas DataFrame with List.mp4 |
22.57MB |
| 1. Datasets on Kaggle.mp4 |
133.23MB |
| 1. Data Types in Python.mp4 |
47.07MB |
| 1. Data Visualisation - Matplotlib Files.html |
170B |
| 1. Decision Tree Algorithm Theory.mp4 |
35.75MB |
| 1. Dropping Columns with Low Correlation.mp4 |
26.83MB |
| 1. Element Selection Operations in Pandas DataFrames Lesson 1.mp4 |
29.90MB |
| 1. Examining Missing Values.mp4 |
45.79MB |
| 1. Examining the Code Section in Kaggle Lesson 1.mp4 |
79.53MB |
| 1. Examining the Data Set 3.mp4 |
39.11MB |
| 1. First Step to the Hearth Attack Prediction Project.mp4 |
117.14MB |
| 1. Hierarchical Clustering Algorithm Theory.mp4 |
28.55MB |
| 1. Hyperparameter Optimization Theory.mp4 |
33.14MB |
| 1. Indexing Numpy Arrays,.mp4 |
26.56MB |
| 1. Installing Anaconda Distribution for Windows.mp4 |
118.32MB |
| 1. Introduction to Data Visualization with Python.mp4 |
12.85MB |
| 1. Introduction to NumPy Library.mp4 |
45.27MB |
| 1. Introduction to Pandas Library.mp4 |
33.93MB |
| 1. K-Fold Cross-Validation Theory.mp4 |
17.45MB |
| 1. K Means Clustering Algorithm Theory.mp4 |
17.13MB |
| 1. K Nearest Neighbors Algorithm Theory.mp4 |
28.66MB |
| 1. Linear Regression Algorithm Theory in Machine Learning A-Z.mp4 |
34.06MB |
| 1. Loading a Dataset from the Seaborn Library.mp4 |
37.72MB |
| 1. Logic of Object Oriented Programming.mp4 |
17.38MB |
| 1. Logistic Regression.mp4 |
29.34MB |
| 1. Multi-Index and Index Hierarchy in Pandas DataFrames.mp4 |
42.66MB |
| 1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4 |
80.35MB |
| 1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 |
49.37MB |
| 1. Operations with Comparison Operators.mp4 |
21.14MB |
| 1. Principal Component Analysis (PCA) Theory.mp4 |
37.96MB |
| 1. Project Conclusion and Sharing.mp4 |
28.66MB |
| 1. Random Forest Algorithm Theory.mp4 |
22.89MB |
| 1. Required Python Libraries.mp4 |
63.55MB |
| 1. Reshaping a NumPy Array Reshape() Function.mp4 |
26.16MB |
| 1. Support Vector Machine Algorithm Theory.mp4 |
21.84MB |
| 1. Unsupervised Learning Overview.mp4 |
16.91MB |
| 1. User Page Review on Kaggle.mp4 |
81.50MB |
| 1. What is Bias Variance Trade-Off.mp4 |
55.03MB |
| 1. What is Discussion on Kaggle.mp4 |
40.63MB |
| 1. What is Geoplotlib.mp4 |
34.18MB |
| 1. What is Kaggle.mp4 |
129.67MB |
| 1. What is Logistic Regression Algorithm in Machine Learning.mp4 |
27.84MB |
| 1. What is Machine Learning.mp4 |
27.58MB |
| 1. What is Matplotlib.mp4 |
19.06MB |
| 1. What is Seaborn.mp4 |
13.59MB |
| 1. What is Supervised Learning in Machine Learning.mp4 |
31.69MB |
| 1. What is the Recommender System Part 1.mp4 |
23.04MB |
| 10 |
848.25KB |
| 10. Exercise - Solution in Python.mp4 |
51.89MB |
| 10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 |
11.45MB |
| 10. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 |
68.08MB |
| 10. Quiz.html |
205B |
| 10. Quiz.html |
205B |
| 10. Quiz.html |
205B |
| 100 |
1.15MB |
| 101 |
1.32MB |
| 102 |
1.37MB |
| 103 |
309.59KB |
| 104 |
669.79KB |
| 105 |
831.77KB |
| 106 |
912.72KB |
| 107 |
1.15MB |
| 108 |
1.28MB |
| 109 |
1.39MB |
| 11 |
986.47KB |
| 11. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.mp4 |
38.07MB |
| 11. Quiz.html |
205B |
| 11. Separating Data into Test and Training Set.mp4 |
29.75MB |
| 110 |
1.64MB |
| 111 |
1.71MB |
| 112 |
1.80MB |
| 113 |
1.93MB |
| 114 |
41.38KB |
| 115 |
284.32KB |
| 116 |
455.71KB |
| 117 |
768.65KB |
| 118 |
1.64MB |
| 119 |
1.76MB |
| 12 |
1.06MB |
| 12. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.mp4 |
35.47MB |
| 12. Quiz.html |
205B |
| 120 |
1.94MB |
| 121 |
164.19KB |
| 122 |
252.49KB |
| 123 |
276.16KB |
| 124 |
293.71KB |
| 125 |
311.69KB |
| 126 |
373.42KB |
| 127 |
423.68KB |
| 128 |
494.34KB |
| 129 |
546.29KB |
| 13 |
191.13KB |
| 13. Relationships between variables (Analysis with Heatmap) Lesson 1.mp4 |
36.36MB |
| 130 |
619.41KB |
| 131 |
820.34KB |
| 132 |
989.96KB |
| 133 |
1.11MB |
| 134 |
1.23MB |
| 135 |
1.33MB |
| 136 |
1.39MB |
| 137 |
1.42MB |
| 138 |
1.46MB |
| 139 |
1.73MB |
| 14 |
1.07MB |
| 14. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 |
90.67MB |
| 140 |
1.82MB |
| 141 |
1.94MB |
| 142 |
69.17KB |
| 143 |
426.89KB |
| 144 |
880.54KB |
| 145 |
1.33MB |
| 146 |
1.98MB |
| 147 |
165.72KB |
| 148 |
322.09KB |
| 149 |
482.45KB |
| 15 |
1.74MB |
| 15. Quiz.html |
205B |
| 150 |
602.33KB |
| 151 |
618.01KB |
| 152 |
764.37KB |
| 153 |
1.45MB |
| 154 |
1.79MB |
| 155 |
45.58KB |
| 156 |
104.83KB |
| 157 |
114.93KB |
| 158 |
225.64KB |
| 159 |
252.55KB |
| 16 |
1.16MB |
| 160 |
365.79KB |
| 161 |
512.72KB |
| 162 |
676.39KB |
| 163 |
800.91KB |
| 164 |
990.45KB |
| 165 |
1.07MB |
| 166 |
1.11MB |
| 167 |
1.34MB |
| 168 |
1.34MB |
| 169 |
1.45MB |
| 17 |
1.76MB |
| 170 |
1.63MB |
| 171 |
1.69MB |
| 172 |
1.78MB |
| 173 |
166.37KB |
| 174 |
251.17KB |
| 175 |
430.23KB |
| 176 |
638.92KB |
| 177 |
1.17MB |
| 178 |
1.44MB |
| 179 |
1.84MB |
| 18 |
641.91KB |
| 180 |
1.98MB |
| 181 |
57.82KB |
| 182 |
304.77KB |
| 183 |
847.48KB |
| 184 |
924.31KB |
| 185 |
1.42MB |
| 186 |
1.48MB |
| 187 |
1.55MB |
| 188 |
1.80MB |
| 189 |
1.85MB |
| 19 |
1.31MB |
| 190 |
1.91MB |
| 191 |
1.94MB |
| 192 |
1.99MB |
| 193 |
56.19KB |
| 194 |
114.99KB |
| 195 |
984.28KB |
| 196 |
1.11MB |
| 197 |
1.43MB |
| 198 |
1.73MB |
| 199 |
1.89MB |
| 2 |
110.81KB |
| 2. Arithmetic Operations in Numpy.mp4 |
71.82MB |
| 2. Competitions on Kaggle Lesson 2.mp4 |
191.68MB |
| 2. Constructor in Object Oriented Programming (OOP).mp4 |
35.84MB |
| 2. Controlling Figure Aesthetics in Seaborn.mp4 |
41.82MB |
| 2. Creating a Pandas Series with a Dictionary.mp4 |
18.29MB |
| 2. Creating NumPy Array with Zeros() Function.mp4 |
24.06MB |
| 2. Creating Pandas DataFrame with NumPy Array.mp4 |
12.10MB |
| 2. Cross Validation.mp4 |
30.21MB |
| 2. Data Entry with Csv and Txt Files.mp4 |
64.34MB |
| 2. Data Visualisation - Seaborn Files.html |
170B |
| 2. Decision Tree Algorithm with Python Part 1.mp4 |
31.53MB |
| 2. Element Selection in Multi-Indexed DataFrames.mp4 |
24.58MB |
| 2. Element Selection Operations in Pandas DataFrames Lesson 2.mp4 |
31.84MB |
| 2. Examining the Code Section in Kaggle Lesson 2.mp4 |
105.81MB |
| 2. Examining the Data Set 1.mp4 |
42.90MB |
| 2. Examining Unique Values.mp4 |
44.54MB |
| 2. Example - 1.mp4 |
38.85MB |
| 2. FAQ about Kaggle.html |
10.94KB |
| 2. FAQ about Machine Learning, Data Science.html |
15.29KB |
| 2. FAQ regarding Data Visualization, Python.html |
8.59KB |
| 2. Hierarchical Clustering Algorithm with Python Part 2.mp4 |
35.52MB |
| 2. Hyperparameter Optimization with Python.mp4 |
47.47MB |
| 2. Identifying the Largest Element of a Numpy Array.mp4 |
15.12MB |
| 2. K-Fold Cross-Validation with Python.mp4 |
34.67MB |
| 2. K Means Clustering Algorithm with Python Part 1.mp4 |
29.96MB |
| 2. K Nearest Neighbors Algorithm with Python Part 1.mp4 |
35.03MB |
| 2. Linear Regression Algorithm With Python Part 1.mp4 |
76.17MB |
| 2. Loading the Statistics Dataset in Data Science.mp4 |
10.00MB |
| 2. Logistic Regression Algorithm with Python Part 1.mp4 |
72.22MB |
| 2. Machine Learning Model Performance Evaluation Classification Error Metrics.mp4 |
100.26MB |
| 2. Machine Learning Terminology.mp4 |
14.03MB |
| 2. Merge Pandas Dataframes Merge() Function Lesson 1.mp4 |
57.29MB |
| 2. Notebook Project Files Link regarding NumPy Python Programming Language Library.html |
155B |
| 2. Numeric Variables (Analysis with Distplot) Lesson 2.mp4 |
19.75MB |
| 2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 |
35.64MB |
| 2. Operators in Python.mp4 |
35.71MB |
| 2. Pandas Project Files Link.html |
180B |
| 2. Pivot Tables in Pandas Library.mp4 |
54.23MB |
| 2. Principal Component Analysis (PCA) with Python Part 1.mp4 |
26.02MB |
| 2. Quiz.html |
205B |
| 2. Quiz.html |
205B |
| 2. Quiz.html |
205B |
| 2. Quiz.html |
205B |
| 2. Quiz.html |
205B |
| 2. Random Forest Algorithm with Pyhon Part 1.mp4 |
38.61MB |
| 2. Ranking Among Users on Kaggle.mp4 |
107.04MB |
| 2. Removing Rows and Columns from Pandas Data frames.mp4 |
15.56MB |
| 2. Slicing One-Dimensional Numpy Arrays.mp4 |
22.27MB |
| 2. Support Vector Machine Algorithm with Python Part 1.mp4 |
35.59MB |
| 2. The Power of NumPy.mp4 |
59.87MB |
| 2. Treasure in The Kaggle.mp4 |
74.64MB |
| 2. Using Pyplot.mp4 |
28.22MB |
| 2. Visualizing Outliers.mp4 |
34.89MB |
| 2. What is the Recommender System Part 2.mp4 |
17.96MB |
| 20 |
1.33MB |
| 200 |
23.90KB |
| 201 |
161.56KB |
| 202 |
164.19KB |
| 203 |
875.85KB |
| 204 |
1.10MB |
| 205 |
1.51MB |
| 206 |
109.79KB |
| 207 |
261.07KB |
| 208 |
267.33KB |
| 209 |
434.91KB |
| 21 |
5.05KB |
| 210 |
960.57KB |
| 211 |
1.06MB |
| 212 |
1.71MB |
| 213 |
1.80MB |
| 214 |
40.42KB |
| 215 |
565.19KB |
| 216 |
630.45KB |
| 217 |
891.30KB |
| 218 |
1000.74KB |
| 219 |
1.09MB |
| 22 |
1.88MB |
| 220 |
1.54MB |
| 221 |
122.86KB |
| 222 |
161.05KB |
| 223 |
198.82KB |
| 224 |
454.09KB |
| 225 |
905.46KB |
| 226 |
1.28MB |
| 227 |
1.97MB |
| 228 |
416.65KB |
| 229 |
1.15MB |
| 23 |
1.94MB |
| 230 |
1.35MB |
| 231 |
1.45MB |
| 232 |
1.90MB |
| 233 |
1.90MB |
| 234 |
30.80KB |
| 235 |
566.28KB |
| 236 |
837.92KB |
| 237 |
1.83MB |
| 238 |
2.04KB |
| 239 |
1.54MB |
| 24 |
508.79KB |
| 240 |
1.58MB |
| 25 |
555.72KB |
| 26 |
882.98KB |
| 27 |
1.65MB |
| 28 |
480.94KB |
| 29 |
1.49MB |
| 3 |
790.26KB |
| 3. Aggregation Functions in Pandas DataFrames.mp4 |
90.69MB |
| 3. Blog and Documentation Sections.mp4 |
40.85MB |
| 3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 |
74.74MB |
| 3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 |
24.15MB |
| 3. Conditionals in Python.mp4 |
41.23MB |
| 3. Creating NumPy Array with Ones() Function.mp4 |
15.88MB |
| 3. Creating Pandas DataFrame with Dictionary.mp4 |
15.84MB |
| 3. Creating Pandas Series with NumPy Array.mp4 |
11.97MB |
| 3. Data Entry with Excel Files.mp4 |
21.84MB |
| 3. Data Visualisation - Geoplotlib.html |
168B |
| 3. Dealing with Outliers – Trtbps Variable Lesson 1.mp4 |
42.82MB |
| 3. Decision Tree Algorithm with Python Part 2.mp4 |
48.92MB |
| 3. Detecting Least Element of Numpy Array Min(), Ar.mp4 |
10.17MB |
| 3. Evaluating Performance Regression Error Metrics in Python.mp4 |
45.70MB |
| 3. Examining the Code Section in Kaggle Lesson 3.mp4 |
159.89MB |
| 3. Example - 2.mp4 |
81.14MB |
| 3. Example in Seaborn.mp4 |
54.90MB |
| 3. Hierarchical Clustering Algorithm with Python Part 2.mp4 |
28.89MB |
| 3. Initial analysis on the dataset.mp4 |
63.96MB |
| 3. Installing Anaconda Distribution for MacOs.mp4 |
46.31MB |
| 3. K Means Clustering Algorithm with Python Part 2.mp4 |
29.64MB |
| 3. K Nearest Neighbors Algorithm with Python Part 2.mp4 |
59.37MB |
| 3. Linear Regression Algorithm With Python Part 2.mp4 |
106.94MB |
| 3. Logistic Regression Algorithm with Python Part 2.mp4 |
81.46MB |
| 3. Machine Learning Project Files.html |
254B |
| 3. Merge Pandas Dataframes Merge() Function Lesson 2.mp4 |
30.55MB |
| 3. Methods in Object Oriented Programming (OOP).mp4 |
25.10MB |
| 3. Notebook Design to be Used in the Project.mp4 |
104.93MB |
| 3. Null Values in Pandas Dataframes.mp4 |
66.96MB |
| 3. Principal Component Analysis (PCA) with Python Part 2.mp4 |
8.42MB |
| 3. Publishing Notebooks on Kaggle.mp4 |
38.20MB |
| 3. Pyplot – Pylab - Matplotlib.mp4 |
28.37MB |
| 3. Quiz.html |
205B |
| 3. Quiz.html |
205B |
| 3. Quiz.html |
205B |
| 3. Random Forest Algorithm with Pyhon Part 2.mp4 |
38.72MB |
| 3. Registering on Kaggle and Member Login Procedures.mp4 |
43.48MB |
| 3. Roc Curve and Area Under Curve (AUC).mp4 |
41.71MB |
| 3. Selecting Elements Using the xs() Function in Multi-Indexed DataFrames.mp4 |
31.25MB |
| 3. Separating variables (Numeric or Categorical).mp4 |
15.81MB |
| 3. Slicing Two-Dimensional Numpy Arrays.mp4 |
34.27MB |
| 3. Statistical Operations in Numpy.mp4 |
32.02MB |
| 3. Support Vector Machine Algorithm with Python Part 2.mp4 |
41.72MB |
| 3. Top Level Element Selection in Pandas DataFramesLesson 1.mp4 |
38.29MB |
| 30 |
1.83MB |
| 31 |
686.80KB |
| 32 |
1.26MB |
| 33 |
1.36MB |
| 34 |
1.78MB |
| 35 |
185.58KB |
| 36 |
1.72MB |
| 37 |
117.35KB |
| 38 |
1.92MB |
| 39 |
1.04MB |
| 4 |
341.19KB |
| 4. 6 Article Advice And Links about Numpy, Numpy Pyhon.html |
4.19KB |
| 4. Assigning Value to One-Dimensional Arrays.mp4 |
18.20MB |
| 4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 |
84.06MB |
| 4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4 |
56.27MB |
| 4. Color Palettes in Seaborn.mp4 |
48.32MB |
| 4. Concatenating Numpy Arrays Concatenate() Functio.mp4 |
38.36MB |
| 4. Creating NumPy Array with Full() Function.mp4 |
11.18MB |
| 4. Dealing with Outliers – Trtbps Variable Lesson 2.mp4 |
43.91MB |
| 4. Decision Tree Algorithm with Python Part 3.mp4 |
14.72MB |
| 4. Dropping Null Values Dropna() Function.mp4 |
34.54MB |
| 4. Examining Statistics of Variables.mp4 |
91.37MB |
| 4. Examining the Data Set 2.mp4 |
46.58MB |
| 4. Examining the Properties of Pandas DataFrames.mp4 |
25.94MB |
| 4. Example - 3.mp4 |
51.28MB |
| 4. FAQ regarding Python.html |
6.23KB |
| 4. Figure, Subplot and Axex.mp4 |
69.89MB |
| 4. Hyperparameter Optimization (with GridSearchCV).mp4 |
58.77MB |
| 4. Inheritance in Object Oriented Programming (OOP).mp4 |
34.58MB |
| 4. K Means Clustering Algorithm with Python Part 3.mp4 |
27.75MB |
| 4. K Nearest Neighbors Algorithm with Python Part 3.mp4 |
31.40MB |
| 4. Linear Regression Algorithm With Python Part 3.mp4 |
70.28MB |
| 4. Logistic Regression Algorithm with Python Part 3.mp4 |
47.35MB |
| 4. Loops in Python.mp4 |
58.81MB |
| 4. Machine Learning With Python.mp4 |
92.24MB |
| 4. Merge Pandas Dataframes Merge() Function Lesson 3.mp4 |
60.17MB |
| 4. Object Types in Series.mp4 |
19.58MB |
| 4. Outputting as an CSV Extension.mp4 |
35.70MB |
| 4. Principal Component Analysis (PCA) with Python Part 3.mp4 |
37.25MB |
| 4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html |
108B |
| 4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html |
97B |
| 4. Quiz.html |
205B |
| 4. Quiz.html |
205B |
| 4. Quiz.html |
205B |
| 4. Quiz.html |
205B |
| 4. Solving Second-Degree Equations with NumPy.mp4 |
24.20MB |
| 4. Support Vector Machine Algorithm with Python Part 3.mp4 |
34.77MB |
| 4. Top Level Element Selection in Pandas DataFramesLesson 2.mp4 |
31.41MB |
| 4. What Should Be Done to Achieve Success in Kaggle.mp4 |
58.48MB |
| 40 |
1.66MB |
| 41 |
44.45KB |
| 42 |
164.06KB |
| 43 |
455.96KB |
| 44 |
724.81KB |
| 45 |
1.30MB |
| 46 |
1.83MB |
| 47 |
1.90MB |
| 48 |
137.74KB |
| 49 |
642.38KB |
| 5 |
1.13MB |
| 5. Assigning Value to Two-Dimensional Array.mp4 |
35.40MB |
| 5. Basic Plots in Seaborn.mp4 |
98.84MB |
| 5. Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes.mp4 |
88.12MB |
| 5. Creating NumPy Array with Arange() Function.mp4 |
12.10MB |
| 5. Dealing with Outliers – Thalach Variable.mp4 |
36.24MB |
| 5. Decision Tree Algorithm.mp4 |
25.70MB |
| 5. Decision Tree Algorithm with Python Part 4.mp4 |
42.49MB |
| 5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4 |
28.31MB |
| 5. Examining the Missing Data According to the Analysis Result.mp4 |
53.78MB |
| 5. Examining the Primary Features of the Pandas Seri.mp4 |
18.94MB |
| 5. Examining the Project Topic.mp4 |
76.51MB |
| 5. FAQ regarding Machine Learning.html |
6.59KB |
| 5. Figure Customization.mp4 |
63.29MB |
| 5. Filling Null Values Fillna() Function.mp4 |
51.62MB |
| 5. Getting to Know the Kaggle Homepage.mp4 |
122.93MB |
| 5. Installing Anaconda Distribution for Linux.mp4 |
114.75MB |
| 5. K Means Clustering Algorithm with Python Part 4.mp4 |
29.03MB |
| 5. Linear Regression Algorithm With Python Part 4.mp4 |
90.00MB |
| 5. Lists, Tuples, Dictionaries and Sets in pyhton.mp4 |
75.33MB |
| 5. Logistic Regression Algorithm with Python Part 4.mp4 |
47.17MB |
| 5. Merge Pandas Dataframes Merge() Function Lesson 4.mp4 |
40.68MB |
| 5. Outputting as an Excel File.mp4 |
19.74MB |
| 5. Overriding and Overloading in Object Oriented Programming (OOP).mp4 |
62.70MB |
| 5. Quiz.html |
205B |
| 5. Quiz.html |
205B |
| 5. Quiz.html |
205B |
| 5. Quiz.html |
205B |
| 5. Quiz.html |
205B |
| 5. Quiz.html |
205B |
| 5. Splitting One-Dimensional Numpy Arrays The Split.mp4 |
20.90MB |
| 5. Support Vector Machine Algorithm with Python Part 4.mp4 |
37.55MB |
| 5. Top Level Element Selection in Pandas DataFramesLesson 3.mp4 |
22.11MB |
| 50 |
1.19MB |
| 51 |
1.23MB |
| 52 |
1.52MB |
| 53 |
723.58KB |
| 54 |
1.73MB |
| 55 |
1.95MB |
| 56 |
991.04KB |
| 57 |
1.10MB |
| 58 |
1.18MB |
| 59 |
1.77MB |
| 6 |
1.07MB |
| 6. Advanced Aggregation Functions Aggregate() Function.mp4 |
29.22MB |
| 6. Creating NumPy Array with Eye() Function.mp4 |
12.55MB |
| 6. Data Type Operators and Methods in Python.mp4 |
43.86MB |
| 6. Dealing with Outliers – Oldpeak Variable.mp4 |
36.06MB |
| 6. Decision Tree Algorithm with Python Part 5.mp4 |
32.67MB |
| 6. Element Selection with Conditional Operations in.mp4 |
46.37MB |
| 6. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4 |
47.14MB |
| 6. Fancy Indexing of One-Dimensional Arrrays.mp4 |
20.49MB |
| 6. Joining Pandas Dataframes Join() Function.mp4 |
56.05MB |
| 6. Logistic Regression Algorithm with Python Part 5.mp4 |
39.35MB |
| 6. Most Applied Methods on Pandas Series.mp4 |
48.21MB |
| 6. Multi-Plots in Seaborn.mp4 |
42.98MB |
| 6. Plot Customization.mp4 |
27.38MB |
| 6. quiz.html |
205B |
| 6. Quiz.html |
205B |
| 6. Quiz.html |
205B |
| 6. Quiz.html |
205B |
| 6. Quiz.html |
205B |
| 6. Quiz.html |
205B |
| 6. Quiz.html |
205B |
| 6. Recognizing Variables In Dataset.mp4 |
126.87MB |
| 6. Setting Index in Pandas DataFrames.mp4 |
39.70MB |
| 6. Splitting Two-Dimensional Numpy Arrays Split(),.mp4 |
35.73MB |
| 6. Support Vector Machine Algorithm.mp4 |
24.52MB |
| 60 |
229.28KB |
| 61 |
1.11MB |
| 62 |
1.35MB |
| 63 |
1.86MB |
| 64 |
117.15KB |
| 65 |
385.56KB |
| 66 |
739.66KB |
| 67 |
649.26KB |
| 68 |
1.08MB |
| 69 |
1.68MB |
| 7 |
1.68MB |
| 7. Advanced Aggregation Functions Filter() Function.mp4 |
24.45MB |
| 7. Creating NumPy Array with Linspace() Function.mp4 |
7.34MB |
| 7. Determining Distributions of Numeric Variables.mp4 |
25.17MB |
| 7. Fancy Indexing of Two-Dimensional Arrrays.mp4 |
45.75MB |
| 7. Feature Scaling with the Robust Scaler Method.mp4 |
35.20MB |
| 7. Grid, Spines, Ticks.mp4 |
23.89MB |
| 7. Indexing and Slicing Pandas Series.mp4 |
29.89MB |
| 7. Modules in Python.mp4 |
23.95MB |
| 7. Quiz.html |
205B |
| 7. Quiz.html |
205B |
| 7. Quiz.html |
205B |
| 7. Quiz.html |
205B |
| 7. Quiz.html |
205B |
| 7. Quiz.html |
205B |
| 7. Random Forest Algorithm.mp4 |
29.78MB |
| 7. Regression Plots and Squarify in Seaborn.mp4 |
60.10MB |
| 7. Sorting Numpy Arrays Sort() Function.mp4 |
17.02MB |
| 70 |
1.79MB |
| 71 |
545.10KB |
| 72 |
666.54KB |
| 73 |
853.54KB |
| 74 |
878.24KB |
| 75 |
932.77KB |
| 76 |
957.13KB |
| 77 |
1.42MB |
| 78 |
1.63MB |
| 79 |
1.69MB |
| 8 |
884.22KB |
| 8. Advanced Aggregation Functions Transform() Function.mp4 |
47.09MB |
| 8. Basic Plots in Matplotlib I.mp4 |
111.17MB |
| 8. Combining Fancy Index with Normal Indexing.mp4 |
12.65MB |
| 8. Creating a New DataFrame with the Melt() Function.mp4 |
52.89MB |
| 8. Creating NumPy Array with Random() Function.mp4 |
43.30MB |
| 8. Functions in Python.mp4 |
28.93MB |
| 8. Hyperparameter Optimization (with GridSearchCV).mp4 |
52.65MB |
| 8. Quiz.html |
205B |
| 8. Quiz.html |
205B |
| 8. Quiz.html |
205B |
| 8. Transformation Operations on Unsymmetrical Data.mp4 |
24.01MB |
| 80 |
216.61KB |
| 81 |
259.36KB |
| 82 |
305.68KB |
| 83 |
750.92KB |
| 84 |
1.46MB |
| 85 |
89.20KB |
| 86 |
143.50KB |
| 87 |
527.40KB |
| 88 |
719.29KB |
| 89 |
1.02MB |
| 9 |
1.25MB |
| 9. Advanced Aggregation Functions Apply() Function.mp4 |
41.42MB |
| 9. Applying One Hot Encoding Method to Categorical Variables.mp4 |
24.09MB |
| 9. Basic Plots in Matplotlib II.mp4 |
54.82MB |
| 9. Combining Fancy Index with Normal Slicing.mp4 |
16.46MB |
| 9. Exercise - Analyse in Python.mp4 |
8.46MB |
| 9. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4 |
41.72MB |
| 9. Properties of NumPy Array.mp4 |
21.98MB |
| 9. Quiz.html |
205B |
| 90 |
1.10MB |
| 91 |
1.18MB |
| 92 |
1.34MB |
| 93 |
1.51MB |
| 94 |
187.42KB |
| 95 |
285.38KB |
| 96 |
291.36KB |
| 97 |
292.83KB |
| 98 |
592.01KB |
| 99 |
784.06KB |
| TutsNode.net.txt |
63B |