Machine Learning & Deep Learning in Python & R

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    27 ANN in R/008 Saving - Restoring Models and Using Callbacks.mp4 216.03 MB
    01 Introduction/002 Course Resources.html 1.23 KB
    02 Setting up Python and Jupyter Notebook/001 Installing Python and Anaconda.mp4 16.27 MB
    02 Setting up Python and Jupyter Notebook/002 This is a milestone!.mp4 20.66 MB
    02 Setting up Python and Jupyter Notebook/003 Opening Jupyter Notebook.mp4 65.19 MB
    02 Setting up Python and Jupyter Notebook/004 Introduction to Jupyter.mp4 40.91 MB
    02 Setting up Python and Jupyter Notebook/005 Arithmetic operators in Python_ Python Basics.mp4 12.74 MB
    02 Setting up Python and Jupyter Notebook/006 Strings in Python_ Python Basics.mp4 64.43 MB
    02 Setting up Python and Jupyter Notebook/007 Lists, Tuples and Directories_ Python Basics.mp4 60.32 MB
    02 Setting up Python and Jupyter Notebook/008 Working with Numpy Library of Python.mp4 43.87 MB
    02 Setting up Python and Jupyter Notebook/009 Working with Pandas Library of Python.mp4 46.88 MB
    02 Setting up Python and Jupyter Notebook/010 Working with Seaborn Library of Python.mp4 40.36 MB
    03 Setting up R Studio and R crash course/001 Installing R and R studio.mp4 35.71 MB
    03 Setting up R Studio and R crash course/002 Basics of R and R studio.mp4 38.84 MB
    03 Setting up R Studio and R crash course/003 Packages in R.mp4 82.94 MB
    03 Setting up R Studio and R crash course/004 Inputting data part 1_ Inbuilt datasets of R.mp4 40.74 MB
    03 Setting up R Studio and R crash course/005 Inputting data part 2_ Manual data entry.mp4 25.52 MB
    03 Setting up R Studio and R crash course/006 Inputting data part 3_ Importing from CSV or Text files.mp4 60.1 MB
    03 Setting up R Studio and R crash course/007 Creating Barplots in R.mp4 96.73 MB
    03 Setting up R Studio and R crash course/008 Creating Histograms in R.mp4 42.02 MB
    04 Basics of Statistics/001 Types of Data.mp4 21.76 MB
    04 Basics of Statistics/002 Types of Statistics.mp4 10.93 MB
    04 Basics of Statistics/003 Describing data Graphically.mp4 65.39 MB
    04 Basics of Statistics/004 Measures of Centers.mp4 38.57 MB
    04 Basics of Statistics/005 Measures of Dispersion.mp4 22.85 MB
    05 Introduction to Machine Learning/001 Introduction to Machine Learning.mp4 109.17 MB
    05 Introduction to Machine Learning/002 Building a Machine Learning Model.mp4 39.48 MB
    06 Data Preprocessing/001 Gathering Business Knowledge.mp4 22.28 MB
    06 Data Preprocessing/002 Data Exploration.mp4 20.5 MB
    06 Data Preprocessing/003 The Dataset and the Data Dictionary.mp4 69.28 MB
    06 Data Preprocessing/004 Importing Data in Python.mp4 27.83 MB
    06 Data Preprocessing/005 Importing the dataset into R.mp4 13.11 MB
    06 Data Preprocessing/006 Univariate analysis and EDD.mp4 24.18 MB
    06 Data Preprocessing/007 EDD in Python.mp4 61.8 MB
    06 Data Preprocessing/008 EDD in R.mp4 96.98 MB
    06 Data Preprocessing/009 Outlier Treatment.mp4 24.49 MB
    06 Data Preprocessing/010 Outlier Treatment in Python.mp4 70.25 MB
    06 Data Preprocessing/011 Outlier Treatment in R.mp4 30.74 MB
    06 Data Preprocessing/012 Missing Value Imputation.mp4 24.99 MB
    06 Data Preprocessing/013 Missing Value Imputation in Python.mp4 23.42 MB
    06 Data Preprocessing/014 Missing Value imputation in R.mp4 26 MB
    06 Data Preprocessing/015 Seasonality in Data.mp4 17.01 MB
    06 Data Preprocessing/016 Bi-variate analysis and Variable transformation.mp4 100.39 MB
    06 Data Preprocessing/017 Variable transformation and deletion in Python.mp4 44.11 MB
    06 Data Preprocessing/018 Variable transformation in R.mp4 55.42 MB
    06 Data Preprocessing/019 Non-usable variables.mp4 20.24 MB
    06 Data Preprocessing/020 Dummy variable creation_ Handling qualitative data.mp4 36.8 MB
    06 Data Preprocessing/021 Dummy variable creation in Python.mp4 26.53 MB
    06 Data Preprocessing/022 Dummy variable creation in R.mp4 43.98 MB
    06 Data Preprocessing/023 Correlation Analysis.mp4 71.59 MB
    06 Data Preprocessing/024 Correlation Analysis in Python.mp4 55.3 MB
    06 Data Preprocessing/025 Correlation Matrix in R.mp4 83.13 MB
    07 Linear Regression/001 The Problem Statement.mp4 9.37 MB
    07 Linear Regression/002 Basic Equations and Ordinary Least Squares (OLS) method.mp4 43.37 MB
    07 Linear Regression/003 Assessing accuracy of predicted coefficients.mp4 92.11 MB
    07 Linear Regression/004 Assessing Model Accuracy_ RSE and R squared.mp4 43.59 MB
    07 Linear Regression/005 Simple Linear Regression in Python.mp4 63.43 MB
    07 Linear Regression/006 Simple Linear Regression in R.mp4 40.82 MB
    07 Linear Regression/007 Multiple Linear Regression.mp4 34.31 MB
    07 Linear Regression/008 The F - statistic.mp4 55.98 MB
    07 Linear Regression/009 Interpreting results of Categorical variables.mp4 22.5 MB
    07 Linear Regression/010 Multiple Linear Regression in Python.mp4 69.73 MB
    07 Linear Regression/011 Multiple Linear Regression in R.mp4 62.37 MB
    07 Linear Regression/012 Test-train split.mp4 41.88 MB
    07 Linear Regression/013 Bias Variance trade-off.mp4 25.09 MB
    07 Linear Regression/014 Test train split in Python.mp4 44.88 MB
    07 Linear Regression/015 Test-Train Split in R.mp4 75.6 MB
    07 Linear Regression/016 Regression models other than OLS.mp4 16.54 MB
    07 Linear Regression/017 Subset selection techniques.mp4 79.06 MB
    07 Linear Regression/018 Subset selection in R.mp4 63.53 MB
    07 Linear Regression/019 Shrinkage methods_ Ridge and Lasso.mp4 33.34 MB
    07 Linear Regression/020 Ridge regression and Lasso in Python.mp4 128.84 MB
    07 Linear Regression/021 Ridge regression and Lasso in R.mp4 103.43 MB
    07 Linear Regression/022 Heteroscedasticity.mp4 14.49 MB
    08 Classification Models_ Data Preparation/001 The Data and the Data Dictionary.mp4 79 MB
    08 Classification Models_ Data Preparation/002 Data Import in Python.mp4 22.06 MB
    08 Classification Models_ Data Preparation/003 Importing the dataset into R.mp4 13.46 MB
    08 Classification Models_ Data Preparation/004 EDD in Python.mp4 77.62 MB
    08 Classification Models_ Data Preparation/005 EDD in R.mp4 66.52 MB
    08 Classification Models_ Data Preparation/006 Outlier treatment in Python.mp4 47.32 MB
    08 Classification Models_ Data Preparation/007 Outlier Treatment in R.mp4 25.37 MB
    08 Classification Models_ Data Preparation/008 Missing Value Imputation in Python.mp4 22.56 MB
    08 Classification Models_ Data Preparation/009 Missing Value imputation in R.mp4 19.05 MB
    08 Classification Models_ Data Preparation/010 Variable transformation and Deletion in Python.mp4 29.25 MB
    08 Classification Models_ Data Preparation/011 Variable transformation in R.mp4 38.02 MB
    08 Classification Models_ Data Preparation/012 Dummy variable creation in Python.mp4 26.37 MB
    08 Classification Models_ Data Preparation/013 Dummy variable creation in R.mp4 44.35 MB
    09 The Three classification models/001 Three Classifiers and the problem statement.mp4 20.33 MB
    09 The Three classification models/002 Why can't we use Linear Regression_.mp4 16.93 MB
    10 Logistic Regression/001 Logistic Regression.mp4 32.92 MB
    10 Logistic Regression/002 Training a Simple Logistic Model in Python.mp4 47.87 MB
    10 Logistic Regression/003 Training a Simple Logistic model in R.mp4 25.56 MB
    10 Logistic Regression/004 Result of Simple Logistic Regression.mp4 26.93 MB
    10 Logistic Regression/005 Logistic with multiple predictors.mp4 8.53 MB
    10 Logistic Regression/006 Training multiple predictor Logistic model in Python.mp4 26.25 MB
    10 Logistic Regression/007 Training multiple predictor Logistic model in R.mp4 15.78 MB
    10 Logistic Regression/008 Confusion Matrix.mp4 21.1 MB
    10 Logistic Regression/009 Creating Confusion Matrix in Python.mp4 51.25 MB
    10 Logistic Regression/010 Evaluating performance of model.mp4 35.16 MB
    10 Logistic Regression/011 Evaluating model performance in Python.mp4 9.01 MB
    10 Logistic Regression/012 Predicting probabilities, assigning classes and making Confusion Matrix in R.mp4 55.69 MB
    11 Linear Discriminant Analysis (LDA)/001 Linear Discriminant Analysis.mp4 40.95 MB
    11 Linear Discriminant Analysis (LDA)/002 LDA in Python.mp4 11.4 MB
    11 Linear Discriminant Analysis (LDA)/003 Linear Discriminant Analysis in R.mp4 74.35 MB
    12 K-Nearest Neighbors classifier/001 Test-Train Split.mp4 39.29 MB
    12 K-Nearest Neighbors classifier/002 Test-Train Split in Python.mp4 33.1 MB
    12 K-Nearest Neighbors classifier/003 Test-Train Split in R.mp4 74.23 MB
    12 K-Nearest Neighbors classifier/004 K-Nearest Neighbors classifier.mp4 75.42 MB
    12 K-Nearest Neighbors classifier/005 K-Nearest Neighbors in Python_ Part 1.mp4 37.23 MB
    12 K-Nearest Neighbors classifier/006 K-Nearest Neighbors in Python_ Part 2.mp4 42.35 MB
    12 K-Nearest Neighbors classifier/007 K-Nearest Neighbors in R.mp4 64.85 MB
    13 Comparing results from 3 models/001 Understanding the results of classification models.mp4 41.64 MB
    13 Comparing results from 3 models/002 Summary of the three models.mp4 22.21 MB
    14 Simple Decision Trees/001 Basics of Decision Trees.mp4 42.64 MB
    14 Simple Decision Trees/002 Understanding a Regression Tree.mp4 43.72 MB
    14 Simple Decision Trees/003 The stopping criteria for controlling tree growth.mp4 13.97 MB
    14 Simple Decision Trees/004 The Data set for this part.mp4 37.26 MB
    14 Simple Decision Trees/005 Importing the Data set into Python.mp4 25.84 MB
    14 Simple Decision Trees/006 Importing the Data set into R.mp4 43.7 MB
    14 Simple Decision Trees/007 Missing value treatment in Python.mp4 17.92 MB
    14 Simple Decision Trees/008 Dummy Variable creation in Python.mp4 24.94 MB
    14 Simple Decision Trees/009 Dependent- Independent Data split in Python.mp4 15.18 MB
    14 Simple Decision Trees/010 Test-Train split in Python.mp4 24.87 MB
    14 Simple Decision Trees/011 Splitting Data into Test and Train Set in R.mp4 43.97 MB
    14 Simple Decision Trees/012 Creating Decision tree in Python.mp4 17.87 MB
    14 Simple Decision Trees/013 Building a Regression Tree in R.mp4 103.33 MB
    14 Simple Decision Trees/014 Evaluating model performance in Python.mp4 16.44 MB
    14 Simple Decision Trees/015 Plotting decision tree in Python.mp4 21.47 MB
    14 Simple Decision Trees/016 Pruning a tree.mp4 18.46 MB
    14 Simple Decision Trees/017 Pruning a tree in Python.mp4 73.5 MB
    14 Simple Decision Trees/018 Pruning a Tree in R.mp4 82.09 MB
    15 Simple Classification Tree/001 Classification tree.mp4 28.2 MB
    15 Simple Classification Tree/002 The Data set for Classification problem.mp4 18.57 MB
    15 Simple Classification Tree/003 Classification tree in Python _ Preprocessing.mp4 45.38 MB
    15 Simple Classification Tree/004 Classification tree in Python _ Training.mp4 82.71 MB
    15 Simple Classification Tree/005 Building a classification Tree in R.mp4 85.1 MB
    15 Simple Classification Tree/006 Advantages and Disadvantages of Decision Trees.mp4 6.86 MB
    16 Ensemble technique 1 - Bagging/001 Ensemble technique 1 - Bagging.mp4 28.14 MB
    16 Ensemble technique 1 - Bagging/002 Ensemble technique 1 - Bagging in Python.mp4 77.3 MB
    16 Ensemble technique 1 - Bagging/003 Bagging in R.mp4 58.95 MB
    17 Ensemble technique 2 - Random Forests/001 Ensemble technique 2 - Random Forests.mp4 18.19 MB
    17 Ensemble technique 2 - Random Forests/002 Ensemble technique 2 - Random Forests in Python.mp4 46.7 MB
    17 Ensemble technique 2 - Random Forests/003 Using Grid Search in Python.mp4 80.66 MB
    17 Ensemble technique 2 - Random Forests/004 Random Forest in R.mp4 30.72 MB
    18 Ensemble technique 3 - Boosting/001 Boosting.mp4 30.58 MB
    18 Ensemble technique 3 - Boosting/002 Ensemble technique 3a - Boosting in Python.mp4 39.87 MB
    18 Ensemble technique 3 - Boosting/003 Gradient Boosting in R.mp4 69.09 MB
    18 Ensemble technique 3 - Boosting/004 Ensemble technique 3b - AdaBoost in Python.mp4 30.53 MB
    18 Ensemble technique 3 - Boosting/005 AdaBoosting in R.mp4 88.67 MB
    18 Ensemble technique 3 - Boosting/006 Ensemble technique 3c - XGBoost in Python.mp4 75 MB
    18 Ensemble technique 3 - Boosting/007 XGBoosting in R.mp4 161.3 MB
    19 Maximum Margin Classifier/001 Content flow.mp4 8.64 MB
    19 Maximum Margin Classifier/002 The Concept of a Hyperplane.mp4 29.42 MB
    19 Maximum Margin Classifier/003 Maximum Margin Classifier.mp4 22.48 MB
    19 Maximum Margin Classifier/004 Limitations of Maximum Margin Classifier.mp4 10.6 MB
    20 Support Vector Classifier/001 Support Vector classifiers.mp4 56.16 MB
    20 Support Vector Classifier/002 Limitations of Support Vector Classifiers.mp4 10.8 MB
    21 Support Vector Machines/001 Kernel Based Support Vector Machines.mp4 40.12 MB
    22 Creating Support Vector Machine Model in Python/001 Regression and Classification Models.mp4 4.03 MB
    22 Creating Support Vector Machine Model in Python/002 The Data set for the Regression problem.mp4 37.2 MB
    22 Creating Support Vector Machine Model in Python/003 Importing data for regression model.mp4 25.84 MB
    22 Creating Support Vector Machine Model in Python/004 X-y Split.mp4 15.18 MB
    22 Creating Support Vector Machine Model in Python/005 Test-Train Split.mp4 24.86 MB
    22 Creating Support Vector Machine Model in Python/006 Standardizing the data.mp4 38.41 MB
    22 Creating Support Vector Machine Model in Python/007 SVM based Regression Model in Python.mp4 67.63 MB
    22 Creating Support Vector Machine Model in Python/008 The Data set for the Classification problem.mp4 18.55 MB
    22 Creating Support Vector Machine Model in Python/009 Classification model - Preprocessing.mp4 45.37 MB
    22 Creating Support Vector Machine Model in Python/010 Classification model - Standardizing the data.mp4 9.72 MB
    22 Creating Support Vector Machine Model in Python/011 SVM Based classification model.mp4 64.12 MB
    22 Creating Support Vector Machine Model in Python/012 Hyper Parameter Tuning.mp4 57.74 MB
    22 Creating Support Vector Machine Model in Python/013 Polynomial Kernel with Hyperparameter Tuning.mp4 22.92 MB
    22 Creating Support Vector Machine Model in Python/014 Radial Kernel with Hyperparameter Tuning.mp4 37.21 MB
    23 Creating Support Vector Machine Model in R/001 Importing Data into R.mp4 53.67 MB
    23 Creating Support Vector Machine Model in R/002 Test-Train Split.mp4 50.48 MB
    23 Creating Support Vector Machine Model in R/003 More about test-train split.html 1.43 KB
    23 Creating Support Vector Machine Model in R/004 Classification SVM model using Linear Kernel.mp4 139.16 MB
    23 Creating Support Vector Machine Model in R/005 Hyperparameter Tuning for Linear Kernel.mp4 60.5 MB
    23 Creating Support Vector Machine Model in R/006 Polynomial Kernel with Hyperparameter Tuning.mp4 83.14 MB
    23 Creating Support Vector Machine Model in R/007 Radial Kernel with Hyperparameter Tuning.mp4 56.68 MB
    23 Creating Support Vector Machine Model in R/008 SVM based Regression Model in R.mp4 106.12 MB
    24 Introduction - Deep Learning/001 Introduction to Neural Networks and Course flow.mp4 29.07 MB
    24 Introduction - Deep Learning/002 Perceptron.mp4 44.75 MB
    24 Introduction - Deep Learning/003 Activation Functions.mp4 34.61 MB
    24 Introduction - Deep Learning/004 Python - Creating Perceptron model.mp4 86.55 MB
    25 Neural Networks - Stacking cells to create network/001 Basic Terminologies.mp4 40.42 MB
    25 Neural Networks - Stacking cells to create network/002 Gradient Descent.mp4 60.34 MB
    25 Neural Networks - Stacking cells to create network/003 Back Propagation.mp4 122.2 MB
    25 Neural Networks - Stacking cells to create network/004 Some Important Concepts.mp4 62.18 MB
    25 Neural Networks - Stacking cells to create network/005 Hyperparameter.mp4 45.35 MB
    26 ANN in Python/001 Keras and Tensorflow.mp4 14.91 MB
    26 ANN in Python/002 Installing Tensorflow and Keras.mp4 20.06 MB
    26 ANN in Python/003 Dataset for classification.mp4 56.19 MB
    26 ANN in Python/004 Normalization and Test-Train split.mp4 44.2 MB
    26 ANN in Python/005 Different ways to create ANN using Keras.mp4 10.81 MB
    26 ANN in Python/006 Building the Neural Network using Keras.mp4 79.11 MB
    26 ANN in Python/007 Compiling and Training the Neural Network model.mp4 81.63 MB
    26 ANN in Python/008 Evaluating performance and Predicting using Keras.mp4 69.91 MB
    26 ANN in Python/009 Building Neural Network for Regression Problem.mp4 155.9 MB
    26 ANN in Python/010 Using Functional API for complex architectures.mp4 92.1 MB
    26 ANN in Python/011 Saving - Restoring Models and Using Callbacks.mp4 151.58 MB
    26 ANN in Python/012 Hyperparameter Tuning.mp4 60.63 MB
    27 ANN in R/001 Installing Keras and Tensorflow.mp4 22.78 MB
    27 ANN in R/002 Data Normalization and Test-Train Split.mp4 111.78 MB
    27 ANN in R/003 Building,Compiling and Training.mp4 130.73 MB
    27 ANN in R/004 Evaluating and Predicting.mp4 99.28 MB
    27 ANN in R/005 ANN with NeuralNets Package.mp4 84.42 MB
    27 ANN in R/006 Building Regression Model with Functional API.mp4 131.12 MB
    27 ANN in R/007 Complex Architectures using Functional API.mp4 79.57 MB
    01 Introduction/001 Introduction.mp4 29.39 MB
    28 CNN - Basics/001 CNN Introduction.mp4 51.15 MB
    28 CNN - Basics/002 Stride.mp4 16.58 MB
    28 CNN - Basics/003 Padding.mp4 31.63 MB
    28 CNN - Basics/004 Filters and Feature maps.mp4 52.71 MB
    28 CNN - Basics/005 Channels.mp4 67.77 MB
    28 CNN - Basics/006 PoolingLayer.mp4 46.87 MB
    29 Creating CNN model in Python/001 CNN model in Python - Preprocessing.mp4 40.63 MB
    29 Creating CNN model in Python/002 CNN model in Python - structure and Compile.mp4 43.25 MB
    29 Creating CNN model in Python/003 CNN model in Python - Training and results.mp4 55.15 MB
    29 Creating CNN model in Python/004 Comparison - Pooling vs Without Pooling in Python.mp4 57.97 MB
    30 Creating CNN model in R/001 CNN on MNIST Fashion Dataset - Model Architecture.mp4 7.35 MB
    30 Creating CNN model in R/002 Data Preprocessing.mp4 67.02 MB
    30 Creating CNN model in R/003 Creating Model Architecture.mp4 71.6 MB
    30 Creating CNN model in R/004 Compiling and training.mp4 32.2 MB
    30 Creating CNN model in R/005 Model Performance.mp4 68.08 MB
    30 Creating CNN model in R/006 Comparison - Pooling vs Without Pooling in R.mp4 44.6 MB
    31 Project _ Creating CNN model from scratch in Python/001 Project - Introduction.mp4 49.39 MB
    31 Project _ Creating CNN model from scratch in Python/002 Data for the project.html 1.1 KB
    31 Project _ Creating CNN model from scratch in Python/003 Project - Data Preprocessing in Python.mp4 71.83 MB
    31 Project _ Creating CNN model from scratch in Python/004 Project - Training CNN model in Python.mp4 65.98 MB
    31 Project _ Creating CNN model from scratch in Python/005 Project in Python - model results.mp4 21.02 MB
    32 Project _ Creating CNN model from scratch/001 Project in R - Data Preprocessing.mp4 87.76 MB
    32 Project _ Creating CNN model from scratch/002 CNN Project in R - Structure and Compile.mp4 46.11 MB
    32 Project _ Creating CNN model from scratch/003 Project in R - Training.mp4 24.58 MB
    32 Project _ Creating CNN model from scratch/004 Project in R - Model Performance.mp4 23.18 MB
    32 Project _ Creating CNN model from scratch/005 Project in R - Data Augmentation.mp4 56.38 MB
    32 Project _ Creating CNN model from scratch/006 Project in R - Validation Performance.mp4 23.69 MB
    33 Project _ Data Augmentation for avoiding overfitting/001 Project - Data Augmentation Preprocessing.mp4 41.41 MB
    33 Project _ Data Augmentation for avoiding overfitting/002 Project - Data Augmentation Training and Results.mp4 53.04 MB
    34 Transfer Learning _ Basics/001 ILSVRC.mp4 20.92 MB
    34 Transfer Learning _ Basics/002 LeNET.mp4 7 MB
    34 Transfer Learning _ Basics/003 VGG16NET.mp4 10.35 MB
    34 Transfer Learning _ Basics/004 GoogLeNet.mp4 21.37 MB
    34 Transfer Learning _ Basics/005 Transfer Learning.mp4 29.99 MB
    34 Transfer Learning _ Basics/006 Project - Transfer Learning - VGG16.mp4 129.09 MB
    35 Transfer Learning in R/001 Project - Transfer Learning - VGG16 (Implementation).mp4 101.57 MB
    35 Transfer Learning in R/002 Project - Transfer Learning - VGG16 (Performance).mp4 64.11 MB
    36 Time Series Analysis and Forecasting/001 Introduction.mp4 12.26 MB
    36 Time Series Analysis and Forecasting/002 Time Series Forecasting - Use cases.mp4 25.91 MB
    36 Time Series Analysis and Forecasting/003 Forecasting model creation - Steps.mp4 10.11 MB
    36 Time Series Analysis and Forecasting/004 Forecasting model creation - Steps 1 (Goal).mp4 34.5 MB
    36 Time Series Analysis and Forecasting/005 Time Series - Basic Notations.mp4 62.48 MB
    37 Time Series - Preprocessing in Python/001 Data Loading in Python.mp4 108.86 MB
    37 Time Series - Preprocessing in Python/002 Time Series - Visualization Basics.mp4 63.72 MB
    37 Time Series - Preprocessing in Python/003 Time Series - Visualization in Python.mp4 165.19 MB
    37 Time Series - Preprocessing in Python/004 Time Series - Feature Engineering Basics.mp4 59.47 MB
    37 Time Series - Preprocessing in Python/005 Time Series - Feature Engineering in Python.mp4 112.69 MB
    37 Time Series - Preprocessing in Python/006 Time Series - Upsampling and Downsampling.mp4 16.95 MB
    37 Time Series - Preprocessing in Python/007 Time Series - Upsampling and Downsampling in Python.mp4 100.67 MB
    37 Time Series - Preprocessing in Python/008 Time Series - Power Transformation.mp4 14.85 MB
    37 Time Series - Preprocessing in Python/009 Moving Average.mp4 38.7 MB
    37 Time Series - Preprocessing in Python/010 Exponential Smoothing.mp4 8.38 MB
    38 Time Series - Important Concepts/001 White Noise.mp4 11.37 MB
    38 Time Series - Important Concepts/002 Random Walk.mp4 21.16 MB
    38 Time Series - Important Concepts/003 Decomposing Time Series in Python.mp4 59.84 MB
    38 Time Series - Important Concepts/004 Differencing.mp4 32.35 MB
    38 Time Series - Important Concepts/005 Differencing in Python.mp4 113 MB
    39 Time Series - Implementation in Python/001 Test Train Split in Python.mp4 57.41 MB
    39 Time Series - Implementation in Python/002 Naive (Persistence) model in Python.mp4 43.37 MB
    39 Time Series - Implementation in Python/003 Auto Regression Model - Basics.mp4 16.88 MB
    39 Time Series - Implementation in Python/004 Auto Regression Model creation in Python.mp4 53.49 MB
    39 Time Series - Implementation in Python/005 Auto Regression with Walk Forward validation in Python.mp4 49.59 MB
    39 Time Series - Implementation in Python/006 Moving Average model -Basics.mp4 24.09 MB
    39 Time Series - Implementation in Python/007 Moving Average model in Python.mp4 56.65 MB
    40 Time Series - ARIMA model/001 ACF and PACF.mp4 41.22 MB
    40 Time Series - ARIMA model/002 ARIMA model - Basics.mp4 21.36 MB
    40 Time Series - ARIMA model/003 ARIMA model in Python.mp4 74.43 MB
    40 Time Series - ARIMA model/004 ARIMA model with Walk Forward Validation in Python.mp4 32.15 MB
    41 Time Series - SARIMA model/001 SARIMA model.mp4 39.02 MB
    41 Time Series - SARIMA model/002 SARIMA model in Python.mp4 66.23 MB
    41 Time Series - SARIMA model/003 Stationary time Series.mp4 5.58 MB
    42 Bonus Section/001 The final milestone!.mp4 11.84 MB
    42 Bonus Section/002 Congratulations & About your certificate.html 2.49 KB

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