14.41 GB | 19min 3s | mp4 | 1920X1080  | 16:9
Genre:eLearning |Language:English

Files Included :
1  Real world use cases of Python.mp4 (53.2 MB)
2  Installation of Anaconda for Windows and macOS.mp4 (97.94 MB)
3  Introduction to Variables.mp4 (128.33 MB)
4  Introduction to Data Types and Type Casting.mp4 (74.31 MB)
5  Scope of Variables.mp4 (165.09 MB)
6  Introduction to Operators.mp4 (414.24 MB)
1  Introduction to Lists and Tuples.mp4 (149.84 MB)
2  Introduction to Sets and Dictionaries.mp4 (209.8 MB)
3  Introduction to Stacks and Queues.mp4 (38.16 MB)
4  Introduction to Space and Time Complexity.mp4 (215.44 MB)
5  Introduction to Sorting Algorithms.mp4 (144.26 MB)
6  Introduction to Searching Algorithms.mp4 (143.52 MB)
1  Introduction to Parameters and Arguments.mp4 (249.7 MB)
2  Introduction to Python Modules.mp4 (97.88 MB)
3  Introduction to Filter, Map, and Zip Functions.mp4 (228.69 MB)
4  Introduction to List, Set and Dictionary Comprehensions.mp4 (173.12 MB)
5  Introduction to Lambda Functions.mp4 (115.18 MB)
6  Introduction to Analytical and Aggregate Functions.mp4 (137.68 MB)
1  Introduction to Strings.mp4 (95.24 MB)
2  Introduction to Important String Functions.mp4 (179.55 MB)
3  Introduction to String Formatting and User Input.mp4 (138.92 MB)
4  Introduction to Meta Characters.mp4 (126.12 MB)
5  Introduction to Built-in Functions for Regular Expressions.mp4 (228.12 MB)
6  Special Characters and Sets for Regular Expressions.mp4 (124.42 MB)
1  Introduction to Conditional Statements.mp4 (69.07 MB)
2  Introduction to For Loops.mp4 (38.87 MB)
3  Introduction to While Loops.mp4 (55.87 MB)
4  Introduction to Break and Continue.mp4 (30.86 MB)
5  Using Conditional Statements in Loops.mp4 (62.7 MB)
6  Nested Loops and Conditional Statements.mp4 (86.09 MB)
1  Introduction to OOPs Concept.mp4 (93.17 MB)
2  Introduction to Inheritance.mp4 (34.89 MB)
3  Introduction to Encapsulation.mp4 (59.16 MB)
4  Introduction to Polymorphism.mp4 (88.22 MB)
5  Introduction to Date and Time Class.mp4 (129.25 MB)
6  Introduction to TimeDelta Class.mp4 (88.97 MB)
1  Introduction to Statistics and its importance.mp4 (166.86 MB)
2  Explain the role of statistics in data analysis.mp4 (40.08 MB)
3  Introduction to Python for Statistical Analysis.mp4 (42.17 MB)
1  Types of Data.mp4 (134.31 MB)
2  Measures of Central Tendency.mp4 (62.69 MB)
3  Measures of Spread.mp4 (79 MB)
4  Measures of Dependence.mp4 (45.1 MB)
5  Measures of Shape and Position.mp4 (158.73 MB)
6  Measures of Standard Scores.mp4 (83.91 MB)
1  Introduction to Basic Probability.mp4 (189.72 MB)
2  Introduction to Set Theory.mp4 (63.26 MB)
3  Introduction to Conditional Probability.mp4 (82.09 MB)
4  Introduction to Bayes Theorem.mp4 (41.36 MB)
5  Introduction to Permutations and Combinations.mp4 (52.04 MB)
6  Introduction to Random Variables.mp4 (87.76 MB)
7  Introduction to Probability Distribution Functions.mp4 (71.91 MB)
1  Introduction to Normal Distribution.mp4 (125.7 MB)
2  Introduction to Skewness and Kurtosis.mp4 (153.01 MB)
3  Introduction to Statistical Transformations.mp4 (226.77 MB)
4  Introduction to Sample and Population Mean.mp4 (78.19 MB)
5  Introduction to Central Limit Theorem.mp4 (24.9 MB)
6  Introduction to Bias and Variance.mp4 (36.68 MB)
7  Introduction to Maximum Likelihood Estimation.mp4 (58.91 MB)
8  Introduction to Confidence Intervals.mp4 (34.89 MB)
9  Introduction to Correlations.mp4 (124.12 MB)
10  Introduction to Sampling Methods.mp4 (116.87 MB)
1  Fundamentals of Hypothesis Testing.mp4 (36.12 MB)
2  Introduction to T Tests.mp4 (213.03 MB)
3  Introduction to Z Tests.mp4 (93.87 MB)
4  Introduction to Chi Squared Tests.mp4 (134.63 MB)
5  Introduction to Anova Tests.mp4 (59.13 MB)
1  Introduction to Numpy Arrays.mp4 (134.42 MB)
2  Introduction to Numpy Operations.mp4 (209.09 MB)
3  Introduction to Pandas.mp4 (42.03 MB)
4  Introduction to Series and DataFrames.mp4 (185.68 MB)
5  Reading CSV and JSON Data using Pandas.mp4 (67.29 MB)
6  Analyzing the Data using Pandas.mp4 (57.89 MB)
1  Indexing, slicing, and Filtering Data.mp4 (269.83 MB)
2  Merging and Concatenation using Pandas.mp4 (132.87 MB)
3  Correlation and Plotting using Pandas.mp4 (243.02 MB)
4  Introduction to Lambda, Map and Apply Functions.mp4 (90.01 MB)
5  Introduction to Grouping Operations using Pandas.mp4 (166.49 MB)
6  Introduction to Cross Tabulation using Pandas.mp4 (65.02 MB)
7  Introduction to Filtering Operations using Pandas.mp4 (83.17 MB)
8  Interactive Grouping and Filtering Operations.mp4 (176.34 MB)
1  Factors for good Data Visualization.mp4 (94.17 MB)
2  Introduction to Univariate Data Visualizations.mp4 (93.26 MB)
3  Introduction to Bivariate Data Visualizations.mp4 (25.14 MB)
4  Plotting two Categorical Variables.mp4 (73.41 MB)
5  Introduction to Multivariate Data Visualizations.mp4 (76.1 MB)
6  Introduction to Heatmaps and Pairplots.mp4 (143.87 MB)
8  Colorscales, Facet Grids, and Sub plots.mp4 (348.12 MB)
9  Introduction to 3D Data Visualization.mp4 (190.23 MB)
10  Introduction to Interactive Data Visualization.mp4 (141.65 MB)
11  Introduction to Maps using Plotly.mp4 (156.97 MB)
12  Introduction to Funnel and Gantt Charts using Plotly.mp4 (146.52 MB)
13  Introduction to Animated Data Visualizations using Plotly.mp4 (205.19 MB)
1  Causes and Impact of Missing Values.mp4 (48.01 MB)
2  Types of Missing Values.mp4 (89.18 MB)
3  When to delete the Missing Values from Data.mp4 (257.15 MB)
4  Imputing Missing Values with Statistical Values.mp4 (145 MB)
5  Imputing Missing Values with Business Logic.mp4 (26.68 MB)
6  Impact of Outliers on ML Models.mp4 (44.84 MB)
7  Dealing with Outliers in an dataset.mp4 (219.33 MB)
1  Introduction to Label and Ordinal Encoding.mp4 (307.33 MB)
2  Introduction to Binary and BaseN Encoding.mp4 (217.94 MB)
3  Introduction to Target Encoding.mp4 (157.51 MB)
1  Introduction to reindex, set index, reset index, and sort index Functions.mp4 (56.49 MB)
2  Introduction to Replace and Droplevel Functions.mp4 (21.04 MB)
3  Introduction to Split and Strip Functions.mp4 (256.98 MB)
4  Introduction to Stack and Unstack Functions.mp4 (76.44 MB)
5  Introduction to Melt, Explode, and Squeeze Functions.mp4 (56.7 MB)
6  Introduction to at time and between time Functions.mp4 (59.11 MB)
7  Introduction to nlargest and nsmallest Functions.mp4 (49.21 MB)
1  Determining how to drop unnecessary columns.mp4 (98.18 MB)
2  Decomposing the Date and Time Features.mp4 (15.85 MB)
3  Decomposing the Categorical Features.mp4 (35.45 MB)
4  Binning the Numerical Features.mp4 (27.44 MB)
5  Aggregation of Features.mp4 (57.48 MB)
1  How Industries are using Machine Learning.mp4 (20.54 MB)
2  Classification vs Regression.mp4 (21.38 MB)
1  Data Transformation with Linear regression.mp4 (74.13 MB)
2  K folds cross validation.mp4 (105.15 MB)
3  Analyzing the Performance of Regression model.mp4 (36.31 MB)
4  R2 and Adjusted R2 intuition.mp4 (30.37 MB)
5  MAE , RMSE , R2 and Adj R2 in code.mp4 (43.34 MB)
6  Industry relevance of Linear regression.mp4 (15.27 MB)
1  What is Regularization and w***s it important.mp4 (36.46 MB)
2  Getting the intuition of Lasso, Ridge and Elastic Net.mp4 (60.55 MB)
3  Applying Lasso, Ridge and Elastic Net in sklearn.mp4 (76.14 MB)
1  Introduction to Logistic Regression.mp4 (59.49 MB)
2  Implementing Logistic Regression using Sklearn.mp4 (167.53 MB)
3  Feature selection using RFECV.mp4 (50.52 MB)
4  Hyperparameter tuning using Grid search.mp4 (260.68 MB)
5  Applying Cross validation.mp4 (35.42 MB)
6  Using accuracy score to analyze the performance of model.mp4 (49.55 MB)
7  Industry Relevance of Logistic Regression.mp4 (13.78 MB)
1  The Kernel Tricks for Support Vector Machines.mp4 (23.67 MB)
2  Implementing Support Vector Machines using Sklearn.mp4 (89.29 MB)
3  Introduction to K Nearest Neighbors.mp4 (19.29 MB)
4  Implementing K Nearest Neighbors using Sklearn.mp4 (22.87 MB)
5  Introduction to Naive and Gaussian Naive Bayes algorithm.mp4 (46.72 MB)
6  Implementing Naive Bayes using Sklearn.mp4 (34.43 MB)
7  When should we apply SVM, KNN, Naive Bayes algorithm.mp4 (18.78 MB)]
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