6.31 GB | 24min 10s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 Introduction.mp4 (45.68 MB)
2 Common Approach to Data Pre-processing.mp4 (100.27 MB)
3 Practical Approach to Data Pre-processing.mp4 (66.26 MB)
4 Practice Exercises.mp4 (9.26 MB)
5 Getting started with Google Colaboratory.mp4 (28.15 MB)
6 Reading your data in Google Colab.mp4 (10.99 MB)
1 Five ways to Handle Imbalanced Data.mp4 (48.25 MB)
1 1 Handling Imabalanced Data Resources.zip (129 KB)
2 Getting started with the Data.mp4 (88.47 MB)
3 Hands-on Imbalance Treatment.mp4 (96.53 MB)
1 The origin of Python.mp4 (36.61 MB)
1 1 Introduction to Python.zip (23.36 KB)
10 Variable assignment.mp4 (3.79 MB)
11 Collections Lists.mp4 (21.97 MB)
12 Collections Tuples.mp4 (7.75 MB)
13 Collections Dictionaries.mp4 (15.53 MB)
14 Collections Sets.mp4 (5.58 MB)
15 Collections Summary.mp4 (2.87 MB)
16 Decision Control.mp4 (41.17 MB)
17 if elif else.mp4 (19.15 MB)
18 Nested If else.mp4 (16.66 MB)
19 Use of logical operators in Decision Control.mp4 (19.18 MB)
2 Python vs Other Languages.mp4 (7.95 MB)
20 if elif ladder and ternary operation.mp4 (23.52 MB)
21 for and while loops.mp4 (27.08 MB)
22 Loops Practice Set 1.mp4 (66.34 MB)
23 Loops Practice Set 2.mp4 (40.21 MB)
24 Applying Loops to a Data.mp4 (49 MB)
25 Getting Started with functions.mp4 (64.4 MB)
26 Using loops and conditionals inside a function.mp4 (66.41 MB)
27 Use of arguments.mp4 (50.95 MB)
28 function inside a function.mp4 (20.29 MB)
29 Use of pass, continue and break.mp4 (53.48 MB)
3 Python for Data Science.mp4 (30.24 MB)
30 Scope of variables.mp4 (15.38 MB)
31 Methods vs Functions.mp4 (39.8 MB)
32 Lambda functions.mp4 (76.35 MB)
33 Extras Variable Names.mp4 (24.24 MB)
34 Extras Mutable vs Immutable Objects.mp4 (31.72 MB)
35 Extras Copy vs Deepcopy.mp4 (15.68 MB)
36 Extras String Formatting.mp4 (41.51 MB)
37 Extras Operator Precedence.mp4 (101.63 MB)
4 Who all use Python.mp4 (18.76 MB)
5 How to learn Python.mp4 (54.61 MB)
6 How much programming knowledge is needed.mp4 (76.61 MB)
7 Variables and Data Types in Python.mp4 (14.98 MB)
8 Operations on variables.mp4 (31.26 MB)
9 Typecasting.mp4 (7.17 MB)
1 Getting started with numpy arrays.mp4 (45.48 MB)
1 1 numpy and pandas resources.zip (44.41 KB)
10 Saving and loading numpy arrays.mp4 (9.88 MB)
11 Getting started with Pandas dataframes.mp4 (59.99 MB)
12 Methods and attributes in Pandas.mp4 (58.28 MB)
13 More Methods and attributes in Pandas.mp4 (75.16 MB)
14 Changing data types.mp4 (18.3 MB)
15 Filtering the data based on conditions.mp4 (45.74 MB)
16 Adding and modifying data.mp4 (69.9 MB)
17 Additional useful Pandas methods.mp4 (38.74 MB)
2 Indexing in numpy arrays.mp4 (55.32 MB)
3 Multidimensional arrays.mp4 (25.57 MB)
4 Using numpy's inbuilt methods.mp4 (73.4 MB)
5 Array operations.mp4 (46.97 MB)
6 Some more inbuilt methods.mp4 (16.01 MB)
7 Generating and accessing random numbers.mp4 (77.58 MB)
8 Modifying elements of an array.mp4 (38.45 MB)
9 More array methods.mp4 (36.92 MB)
1 Univariate Visualization.mp4 (19.1 MB)
1 1 matplotlib and seaborn resources.zip (1.72 MB)
10 Matplotlib Subplots and More Customizations.mp4 (83.64 MB)
11 Seaborn Getting Started with Data.mp4 (30.82 MB)
12 Seaborn Visualizing Univariate Numerical Variables.mp4 (84.17 MB)
13 Seaborn Visualizing Univariate Categorical Variables.mp4 (49.61 MB)
14 Seaborn Scatterplot.mp4 (19.2 MB)
15 Seaborn Conditional Boxplot.mp4 (11.92 MB)
16 Pandas Stacked Bar Chart.mp4 (19.63 MB)
17 Seaborn Multivariate Visualization.mp4 (42.52 MB)
18 Seaborn Customizations.mp4 (53.93 MB)
2 Bivariate Visualization.mp4 (13.58 MB)
3 How many Plots to create.mp4 (16.97 MB)
4 Matplotlib Univariate Analysis.mp4 (72.76 MB)
5 Matplotlib Bivariate Analysis.mp4 (65.58 MB)
6 Matplotlib Customizing Histograms and Barchart.mp4 (77.72 MB)
7 Matplotlib Customizing Boxplot and Piechart.mp4 (58.02 MB)
8 Matplotlib Customizing Stacked Bar Chart.mp4 (20.74 MB)
9 Matplotlib Customizing Line Plots.mp4 (58.05 MB)
1 Use of Central Tendencies.mp4 (48.8 MB)
10 Shift of Origin and Scale.mp4 (34.31 MB)
2 Mean, Median, and Mode.mp4 (54.83 MB)
3 Measures of Dispersion.mp4 (70.22 MB)
4 Sample vs Population.mp4 (19.18 MB)
5 Pearson's Correlation.mp4 (45.6 MB)
6 Pearson's Correlation Handson.mp4 (31.44 MB)
7 Pearson's Correlation Assumptions.mp4 (6.4 MB)
8 Correlation is not Causation.mp4 (6.89 MB)
9 Anscombe's Quartet.mp4 (17.79 MB)
1 Section Intro.mp4 (2.45 MB)
1 1 Feature Scaling Resources.zip (216.32 KB)
10 The RobustScaler.mp4 (36.67 MB)
13 Data Leakage.mp4 (104.05 MB)
14 Practice Exercise Part 1.mp4 (43.9 MB)
14 1 Practice Exercise Part 1.zip (252.88 KB)
15 Solution Practice Exercise Part 1.mp4 (74.06 MB)
2 What is Feature Scaling.mp4 (12.15 MB)
3 Why Feature Scaling is needed.mp4 (26.81 MB)
4 Scaling Treatment Options.mp4 (45.39 MB)
5 Advantages and Disadvantages of Scaling.mp4 (12.97 MB)
6 Getting started with the Data.mp4 (50.99 MB)
7 The Normal Distribution.mp4 (26.6 MB)
8 The StandardScaler.mp4 (19.57 MB)
9 The MinMaxScaler.mp4 (8.79 MB)
1 Section Intro.mp4 (2.05 MB)
1 1 Missing Value Treatment Resources.zip (176.49 KB)
10 The KNN Imputer.mp4 (66.99 MB)
11 The Iterative Imputer.mp4 (53.54 MB)
12 A closer look at Missing Values.mp4 (66.98 MB)
13 Recognizing Missing Values Hands-on.mp4 (61.74 MB)
2 What are missing values.mp4 (31.49 MB)
3 Common mistakes to be avoided.mp4 (24.35 MB)
4 Getting started with the Data.mp4 (72.58 MB)
5 Dropping Missing Values.mp4 (16.13 MB)
6 Filling Missing Values.mp4 (19.13 MB)
7 Forward Fill and Backward Fill.mp4 (16.79 MB)
8 The Simple Imputer.mp4 (37.67 MB)
9 KNN Intuition.mp4 (15.42 MB)
1 Section Intro.mp4 (1.54 MB)
1 1 Outlier Treatment Resources.zip (2.52 MB)
10 Winsorization.mp4 (28.53 MB)
11 Algorithmic Treatment.mp4 (59.83 MB)
13 Practice Exercise Part 2.mp4 (10.19 MB)
13 1 Practice Exercise Part 2.zip (253.77 KB)
14 Solution Practice Exercise Part 2.mp4 (26.31 MB)
2 What are Outliers.mp4 (26.05 MB)
3 Why to treat Outliers.mp4 (37.58 MB)
4 Choosing the Outlier Treatment.mp4 (40.03 MB)
5 Getting started with the Data.mp4 (79.69 MB)
6 Detecting Outliers Using Tukey's Approach.mp4 (26.47 MB)
7 Remove Outlier Rows.mp4 (31.74 MB)
8 Replace Outliers with the Median.mp4 (17.5 MB)
9 Feature Transformation for Outliers.mp4 (31.38 MB)
1 Section Intro.mp4 (2.44 MB)
1 1 Multicollinearity Treatment Resources.zip (326.8 KB)
11 Practice Exercise Part 3.mp4 (5.45 MB)
11 1 Practice Exercise Part 3.zip (461.94 KB)
12 Solution Practice Exercise Part 3.mp4 (56.17 MB)
2 What is Multicollinearity.mp4 (20.5 MB)
3 Why to treat Multicollinearity.mp4 (23.93 MB)
4 Choices for Multicollinearity Treatment.mp4 (4 MB)
5 Common mistakes to be avoided.mp4 (8.33 MB)
6 What is Variance Inflation Factor(VIF).mp4 (23.66 MB)
7 Getting started with the Data.mp4 (49.59 MB)
8 Dropping Correlated Variables.mp4 (71.86 MB)
9 Eliminate Highly Correlated Features using VIF.mp4 (63.66 MB)
1 What is Feature Selection.mp4 (8.62 MB)
1 1 Feature Selection Resources.zip (170.76 KB)
10 Hands-on Select K Best.mp4 (29.76 MB)
11 Hands-on Recursive Feature Elimination.mp4 (27.25 MB)
12 Hands-on Select From Model.mp4 (24 MB)
13 Hands-on Sequential Feature Selector.mp4 (24.06 MB)
2 Variance Threshold.mp4 (14.88 MB)
3 Select K Best.mp4 (20.41 MB)
4 Recursive Feature Elimination.mp4 (3.13 MB)
5 Select From Model.mp4 (5.38 MB)
6 Sequential Feature Selector.mp4 (17.77 MB)
7 Getting started with the data.mp4 (36.87 MB)
8 Supervised Feature Selection.mp4 (17.14 MB)
9 Hands-on Variance Threshold.mp4 (49.56 MB)
1 Section Intro.mp4 (2.35 MB)
1 1 Feature Encoding Resources.zip (67.29 KB)
10 Getting started with the Data.mp4 (30.79 MB)
11 Label Encoder Hands-on.mp4 (9.22 MB)
12 One Hot Encoder Hands-on (sklearn).mp4 (67.77 MB)
13 One Hot Encoder Hands-on (pandas).mp4 (12.2 MB)
14 Encoding Features with High Cardinality.mp4 (54.45 MB)
15 Ordinal Encoder Hands-on.mp4 (16.04 MB)
16 Custom Encoder Hands-on.mp4 (17.82 MB)
17 Target Encoder Hands-on.mp4 (29.68 MB)
19 Practice Exercise Part 4.mp4 (19.55 MB)
19 1 Practice Exercise Part 4.zip (51.36 KB)
2 What is Feature Encoding.mp4 (18.48 MB)
20 Solution Practice Exercise Part 4.mp4 (37.69 MB)
3 Why to perform Feature Encoding.mp4 (5.99 MB)
4 Encoding Choices.mp4 (1.85 MB)
5 Label Encoding.mp4 (11.26 MB)
6 One Hot Encoding.mp4 (23.33 MB)
7 Ordinal and Custom Encoding.mp4 (9.9 MB)
8 Target Encoding.mp4 (26.65 MB)
9 Common mistakes to be avoided.mp4 (17.15 MB)
1 Why to perform Feature Transformation.mp4 (26.89 MB)
2 Choosing the Right Feature Transformation.mp4 (25.06 MB)
3 Transformations to achieve Linearity.mp4 (20.46 MB)
4 Transformations to achieve Normality.mp4 (22.43 MB)
1 What is Anomaly Detection.mp4 (69.78 MB)
1 1 Anomaly Detection Resources.zip (1.26 MB)
2 Anomaly Detection Hands-on.mp4 (257.41 MB)
2 Common Approach to Data Pre-processing.mp4 (100.27 MB)
3 Practical Approach to Data Pre-processing.mp4 (66.26 MB)
4 Practice Exercises.mp4 (9.26 MB)
5 Getting started with Google Colaboratory.mp4 (28.15 MB)
6 Reading your data in Google Colab.mp4 (10.99 MB)
1 Five ways to Handle Imbalanced Data.mp4 (48.25 MB)
1 1 Handling Imabalanced Data Resources.zip (129 KB)
2 Getting started with the Data.mp4 (88.47 MB)
3 Hands-on Imbalance Treatment.mp4 (96.53 MB)
1 The origin of Python.mp4 (36.61 MB)
1 1 Introduction to Python.zip (23.36 KB)
10 Variable assignment.mp4 (3.79 MB)
11 Collections Lists.mp4 (21.97 MB)
12 Collections Tuples.mp4 (7.75 MB)
13 Collections Dictionaries.mp4 (15.53 MB)
14 Collections Sets.mp4 (5.58 MB)
15 Collections Summary.mp4 (2.87 MB)
16 Decision Control.mp4 (41.17 MB)
17 if elif else.mp4 (19.15 MB)
18 Nested If else.mp4 (16.66 MB)
19 Use of logical operators in Decision Control.mp4 (19.18 MB)
2 Python vs Other Languages.mp4 (7.95 MB)
20 if elif ladder and ternary operation.mp4 (23.52 MB)
21 for and while loops.mp4 (27.08 MB)
22 Loops Practice Set 1.mp4 (66.34 MB)
23 Loops Practice Set 2.mp4 (40.21 MB)
24 Applying Loops to a Data.mp4 (49 MB)
25 Getting Started with functions.mp4 (64.4 MB)
26 Using loops and conditionals inside a function.mp4 (66.41 MB)
27 Use of arguments.mp4 (50.95 MB)
28 function inside a function.mp4 (20.29 MB)
29 Use of pass, continue and break.mp4 (53.48 MB)
3 Python for Data Science.mp4 (30.24 MB)
30 Scope of variables.mp4 (15.38 MB)
31 Methods vs Functions.mp4 (39.8 MB)
32 Lambda functions.mp4 (76.35 MB)
33 Extras Variable Names.mp4 (24.24 MB)
34 Extras Mutable vs Immutable Objects.mp4 (31.72 MB)
35 Extras Copy vs Deepcopy.mp4 (15.68 MB)
36 Extras String Formatting.mp4 (41.51 MB)
37 Extras Operator Precedence.mp4 (101.63 MB)
4 Who all use Python.mp4 (18.76 MB)
5 How to learn Python.mp4 (54.61 MB)
6 How much programming knowledge is needed.mp4 (76.61 MB)
7 Variables and Data Types in Python.mp4 (14.98 MB)
8 Operations on variables.mp4 (31.26 MB)
9 Typecasting.mp4 (7.17 MB)
1 Getting started with numpy arrays.mp4 (45.48 MB)
1 1 numpy and pandas resources.zip (44.41 KB)
10 Saving and loading numpy arrays.mp4 (9.88 MB)
11 Getting started with Pandas dataframes.mp4 (59.99 MB)
12 Methods and attributes in Pandas.mp4 (58.28 MB)
13 More Methods and attributes in Pandas.mp4 (75.16 MB)
14 Changing data types.mp4 (18.3 MB)
15 Filtering the data based on conditions.mp4 (45.74 MB)
16 Adding and modifying data.mp4 (69.9 MB)
17 Additional useful Pandas methods.mp4 (38.74 MB)
2 Indexing in numpy arrays.mp4 (55.32 MB)
3 Multidimensional arrays.mp4 (25.57 MB)
4 Using numpy's inbuilt methods.mp4 (73.4 MB)
5 Array operations.mp4 (46.97 MB)
6 Some more inbuilt methods.mp4 (16.01 MB)
7 Generating and accessing random numbers.mp4 (77.58 MB)
8 Modifying elements of an array.mp4 (38.45 MB)
9 More array methods.mp4 (36.92 MB)
1 Univariate Visualization.mp4 (19.1 MB)
1 1 matplotlib and seaborn resources.zip (1.72 MB)
10 Matplotlib Subplots and More Customizations.mp4 (83.64 MB)
11 Seaborn Getting Started with Data.mp4 (30.82 MB)
12 Seaborn Visualizing Univariate Numerical Variables.mp4 (84.17 MB)
13 Seaborn Visualizing Univariate Categorical Variables.mp4 (49.61 MB)
14 Seaborn Scatterplot.mp4 (19.2 MB)
15 Seaborn Conditional Boxplot.mp4 (11.92 MB)
16 Pandas Stacked Bar Chart.mp4 (19.63 MB)
17 Seaborn Multivariate Visualization.mp4 (42.52 MB)
18 Seaborn Customizations.mp4 (53.93 MB)
2 Bivariate Visualization.mp4 (13.58 MB)
3 How many Plots to create.mp4 (16.97 MB)
4 Matplotlib Univariate Analysis.mp4 (72.76 MB)
5 Matplotlib Bivariate Analysis.mp4 (65.58 MB)
6 Matplotlib Customizing Histograms and Barchart.mp4 (77.72 MB)
7 Matplotlib Customizing Boxplot and Piechart.mp4 (58.02 MB)
8 Matplotlib Customizing Stacked Bar Chart.mp4 (20.74 MB)
9 Matplotlib Customizing Line Plots.mp4 (58.05 MB)
1 Use of Central Tendencies.mp4 (48.8 MB)
10 Shift of Origin and Scale.mp4 (34.31 MB)
2 Mean, Median, and Mode.mp4 (54.83 MB)
3 Measures of Dispersion.mp4 (70.22 MB)
4 Sample vs Population.mp4 (19.18 MB)
5 Pearson's Correlation.mp4 (45.6 MB)
6 Pearson's Correlation Handson.mp4 (31.44 MB)
7 Pearson's Correlation Assumptions.mp4 (6.4 MB)
8 Correlation is not Causation.mp4 (6.89 MB)
9 Anscombe's Quartet.mp4 (17.79 MB)
1 Section Intro.mp4 (2.45 MB)
1 1 Feature Scaling Resources.zip (216.32 KB)
10 The RobustScaler.mp4 (36.67 MB)
13 Data Leakage.mp4 (104.05 MB)
14 Practice Exercise Part 1.mp4 (43.9 MB)
14 1 Practice Exercise Part 1.zip (252.88 KB)
15 Solution Practice Exercise Part 1.mp4 (74.06 MB)
2 What is Feature Scaling.mp4 (12.15 MB)
3 Why Feature Scaling is needed.mp4 (26.81 MB)
4 Scaling Treatment Options.mp4 (45.39 MB)
5 Advantages and Disadvantages of Scaling.mp4 (12.97 MB)
6 Getting started with the Data.mp4 (50.99 MB)
7 The Normal Distribution.mp4 (26.6 MB)
8 The StandardScaler.mp4 (19.57 MB)
9 The MinMaxScaler.mp4 (8.79 MB)
1 Section Intro.mp4 (2.05 MB)
1 1 Missing Value Treatment Resources.zip (176.49 KB)
10 The KNN Imputer.mp4 (66.99 MB)
11 The Iterative Imputer.mp4 (53.54 MB)
12 A closer look at Missing Values.mp4 (66.98 MB)
13 Recognizing Missing Values Hands-on.mp4 (61.74 MB)
2 What are missing values.mp4 (31.49 MB)
3 Common mistakes to be avoided.mp4 (24.35 MB)
4 Getting started with the Data.mp4 (72.58 MB)
5 Dropping Missing Values.mp4 (16.13 MB)
6 Filling Missing Values.mp4 (19.13 MB)
7 Forward Fill and Backward Fill.mp4 (16.79 MB)
8 The Simple Imputer.mp4 (37.67 MB)
9 KNN Intuition.mp4 (15.42 MB)
1 Section Intro.mp4 (1.54 MB)
1 1 Outlier Treatment Resources.zip (2.52 MB)
10 Winsorization.mp4 (28.53 MB)
11 Algorithmic Treatment.mp4 (59.83 MB)
13 Practice Exercise Part 2.mp4 (10.19 MB)
13 1 Practice Exercise Part 2.zip (253.77 KB)
14 Solution Practice Exercise Part 2.mp4 (26.31 MB)
2 What are Outliers.mp4 (26.05 MB)
3 Why to treat Outliers.mp4 (37.58 MB)
4 Choosing the Outlier Treatment.mp4 (40.03 MB)
5 Getting started with the Data.mp4 (79.69 MB)
6 Detecting Outliers Using Tukey's Approach.mp4 (26.47 MB)
7 Remove Outlier Rows.mp4 (31.74 MB)
8 Replace Outliers with the Median.mp4 (17.5 MB)
9 Feature Transformation for Outliers.mp4 (31.38 MB)
1 Section Intro.mp4 (2.44 MB)
1 1 Multicollinearity Treatment Resources.zip (326.8 KB)
11 Practice Exercise Part 3.mp4 (5.45 MB)
11 1 Practice Exercise Part 3.zip (461.94 KB)
12 Solution Practice Exercise Part 3.mp4 (56.17 MB)
2 What is Multicollinearity.mp4 (20.5 MB)
3 Why to treat Multicollinearity.mp4 (23.93 MB)
4 Choices for Multicollinearity Treatment.mp4 (4 MB)
5 Common mistakes to be avoided.mp4 (8.33 MB)
6 What is Variance Inflation Factor(VIF).mp4 (23.66 MB)
7 Getting started with the Data.mp4 (49.59 MB)
8 Dropping Correlated Variables.mp4 (71.86 MB)
9 Eliminate Highly Correlated Features using VIF.mp4 (63.66 MB)
1 What is Feature Selection.mp4 (8.62 MB)
1 1 Feature Selection Resources.zip (170.76 KB)
10 Hands-on Select K Best.mp4 (29.76 MB)
11 Hands-on Recursive Feature Elimination.mp4 (27.25 MB)
12 Hands-on Select From Model.mp4 (24 MB)
13 Hands-on Sequential Feature Selector.mp4 (24.06 MB)
2 Variance Threshold.mp4 (14.88 MB)
3 Select K Best.mp4 (20.41 MB)
4 Recursive Feature Elimination.mp4 (3.13 MB)
5 Select From Model.mp4 (5.38 MB)
6 Sequential Feature Selector.mp4 (17.77 MB)
7 Getting started with the data.mp4 (36.87 MB)
8 Supervised Feature Selection.mp4 (17.14 MB)
9 Hands-on Variance Threshold.mp4 (49.56 MB)
1 Section Intro.mp4 (2.35 MB)
1 1 Feature Encoding Resources.zip (67.29 KB)
10 Getting started with the Data.mp4 (30.79 MB)
11 Label Encoder Hands-on.mp4 (9.22 MB)
12 One Hot Encoder Hands-on (sklearn).mp4 (67.77 MB)
13 One Hot Encoder Hands-on (pandas).mp4 (12.2 MB)
14 Encoding Features with High Cardinality.mp4 (54.45 MB)
15 Ordinal Encoder Hands-on.mp4 (16.04 MB)
16 Custom Encoder Hands-on.mp4 (17.82 MB)
17 Target Encoder Hands-on.mp4 (29.68 MB)
19 Practice Exercise Part 4.mp4 (19.55 MB)
19 1 Practice Exercise Part 4.zip (51.36 KB)
2 What is Feature Encoding.mp4 (18.48 MB)
20 Solution Practice Exercise Part 4.mp4 (37.69 MB)
3 Why to perform Feature Encoding.mp4 (5.99 MB)
4 Encoding Choices.mp4 (1.85 MB)
5 Label Encoding.mp4 (11.26 MB)
6 One Hot Encoding.mp4 (23.33 MB)
7 Ordinal and Custom Encoding.mp4 (9.9 MB)
8 Target Encoding.mp4 (26.65 MB)
9 Common mistakes to be avoided.mp4 (17.15 MB)
1 Why to perform Feature Transformation.mp4 (26.89 MB)
2 Choosing the Right Feature Transformation.mp4 (25.06 MB)
3 Transformations to achieve Linearity.mp4 (20.46 MB)
4 Transformations to achieve Normality.mp4 (22.43 MB)
1 What is Anomaly Detection.mp4 (69.78 MB)
1 1 Anomaly Detection Resources.zip (1.26 MB)
2 Anomaly Detection Hands-on.mp4 (257.41 MB)
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