kingers Posted April 22 Report Share Posted April 22 12.41 GB | 20min 16s | mp4 | 1280X720 | 16:9Genre:eLearning |Language:EnglishFiles Included :FileName :1 Overview.mp4 | Size: (20.45 MB)FileName :1 Project - Introduction.mp4 | Size: (47.68 MB)FileName :10 Project in R - Data Augmentation.mp4 | Size: (61.39 MB)FileName :11 Project in R - Validation Performanc.mp4 | Size: (26.77 MB)FileName :12 Project - Data Augmentation Preprocessing.mp4 | Size: (42.62 MB)FileName :13 Project - Data Augmentation Training and Results.mp4 | Size: (56.98 MB)FileName :3 Project - Data Preprocessing in Python.mp4 | Size: (76.01 MB)FileName :4 Project - Training CNN model in Python.mp4 | Size: (68.96 MB)FileName :5 Project in Python - model results.mp4 | Size: (22.18 MB)FileName :6 Project in R - Data Preprocessing.mp4 | Size: (96.68 MB)FileName :7 CNN Project in R - Structure and Compile.mp4 | Size: (51.12 MB)FileName :8 Project in R - Training.mp4 | Size: (27.21 MB)FileName :9 Project in R - Model Performance.mp4 | Size: (25.96 MB)FileName :1 ILSVRC.mp4 | Size: (20.27 MB)FileName :2 LeNET.mp4 | Size: (7.48 MB)FileName :3 VGG16NET.mp4 | Size: (10.05 MB)FileName :4 GoogLeNet.mp4 | Size: (21 MB)FileName :5 Transfer Learning.mp4 | Size: (30.2 MB)FileName :6 Project - Transfer Learning - VGG16.mp4 | Size: (135.62 MB)FileName :7 Project - Transfer Learning - VGG16 (Implementation).mp4 | Size: (111.89 MB)FileName :8 Project - Transfer Learning - VGG16 (Performance).mp4 | Size: (71.64 MB)FileName :1 Introduction.mp4 | Size: (11.96 MB)FileName :2 Time Series Forecasting - Use cases.mp4 | Size: (25.71 MB)FileName :3 Forecasting model creation - Steps.mp4 | Size: (9.57 MB)FileName :4 Forecasting model creation - Steps 1 (Goal).mp4 | Size: (33.16 MB)FileName :5 Time Series - Basic Notations.mp4 | Size: (60.79 MB)FileName :1 Data Loading in Python.mp4 | Size: (110.77 MB)FileName :10 Exponential Smoothing.mp4 | Size: (8.07 MB)FileName :11 White Noise.mp4 | Size: (10.99 MB)FileName :12 Random Walk.mp4 | Size: (20.33 MB)FileName :13 Decomposing Time Series in Python.mp4 | Size: (62.37 MB)FileName :14 Differencing.mp4 | Size: (31.77 MB)FileName :15 Differencing in Python.mp4 | Size: (117.74 MB)FileName :16 Test Train Split in Python.mp4 | Size: (59.07 MB)FileName :17 Naive (Persistence) model in Python.mp4 | Size: (44.29 MB)FileName :18 Auto Regression Model - Basics.mp4 | Size: (16.57 MB)FileName :19 Auto Regression Model creation in Python.mp4 | Size: (55.45 MB)FileName :2 Time Series - Visualization Basics.mp4 | Size: (62.97 MB)FileName :20 Auto Regression with Walk Forward validation in Python.mp4 | Size: (51.54 MB)FileName :21 Moving Average model -Basics.mp4 | Size: (23.67 MB)FileName :22 Moving Average model in Python.mp4 | Size: (58.37 MB)FileName :3 Time Series - Visualization in Python.mp4 | Size: (169.83 MB)FileName :4 Time Series - Feature Engineering Basics.mp4 | Size: (58.46 MB)FileName :5 Time Series - Feature Engineering in Python.mp4 | Size: (116.95 MB)FileName :6 Time Series - Upsampling and Downsampling.mp4 | Size: (16.55 MB)FileName :7 Time Series - Upsampling and Downsampling in Python.mp4 | Size: (102.2 MB)FileName :8 Time Series - Power Transformation.mp4 | Size: (14.67 MB)FileName :9 Moving Average.mp4 | Size: (37.88 MB)FileName :1 ACF and PACF.mp4 | Size: (40.59 MB)FileName :2 ARIMA model - Basics.mp4 | Size: (20.71 MB)FileName :3 ARIMA model in Python.mp4 | Size: (76.55 MB)FileName :4 ARIMA model with Walk Forward Validation in Python.mp4 | Size: (33.13 MB)FileName :1 SARIMA model.mp4 | Size: (38.45 MB)FileName :2 SARIMA model in Python.mp4 | Size: (69.15 MB)FileName :3 Stationary time Series.mp4 | Size: (5.3 MB)FileName :1 Installing Python & Anaconda.mp4 | Size: (16.37 MB)FileName :2 Jupyter Overview.mp4 | Size: (40.03 MB)FileName :3 Python Basics.mp4 | Size: (12.44 MB)FileName :4 Python Basics 2.mp4 | Size: (63.47 MB)FileName :5 Python Basics 3.mp4 | Size: (59.72 MB)FileName :6 Numpy.mp4 | Size: (44.32 MB)FileName :7 Pandas.mp4 | Size: (50.95 MB)FileName :8 Seaborn.mp4 | Size: (42.26 MB)FileName :1 Installing R & Studio.mp4 | Size: (37.59 MB)FileName :2 R & R Studio - Basics.mp4 | Size: (36.95 MB)FileName :3 Packages in R.mp4 | Size: (84.64 MB)FileName :4 Inbuilt datasets of R.mp4 | Size: (41.53 MB)FileName :5 Manual data entry.mp4 | Size: (25.96 MB)FileName :6 Importing from CSV or Text files.mp4 | Size: (61.15 MB)FileName :7 Barplots.mp4 | Size: (98.25 MB)FileName :8 Histograms.mp4 | Size: (42.31 MB)FileName :1 Types of Data.mp4 | Size: (21.73 MB)FileName :2 Types of Statistics.mp4 | Size: (10.57 MB)FileName :3 Describing data Graphically.mp4 | Size: (67.26 MB)FileName :4 Measures of Centers.mp4 | Size: (39.37 MB)FileName :5 Measures of Dispersion.mp4 | Size: (23.55 MB)FileName :1 Introduction to Machine Learning.mp4 | Size: (107.24 MB)FileName :10 EDD in R.mp4 | Size: (99.33 MB)FileName :100 Random Forest in R.mp4 | Size: (30.37 MB)FileName :101 Boosting.mp4 | Size: (29.4 MB)FileName :102 Ensemble technique 3a - Boosting in Python.mp4 | Size: (42.22 MB)FileName :103 Gradient Boosting in R.mp4 | Size: (68.93 MB)FileName :104 Ensemble technique 3b - AdaBoost in Python.mp4 | Size: (33.49 MB)FileName :105 AdaBoosting in R.mp4 | Size: (89.46 MB)FileName :106 Ensemble technique 3c - XGBoost in Python.mp4 | Size: (79.3 MB)FileName :107 XGBoosting in R.mp4 | Size: (163.42 MB)FileName :108 Content Flow.mp4 | Size: (8.36 MB)FileName :109 Concept of a Hyperplane.mp4 | Size: (28.5 MB)FileName :11 Outlier Treatment.mp4 | Size: (23.47 MB)FileName :110 Maximum Margin Classifier.mp4 | Size: (21.99 MB)FileName :111 Limitations of Maximum Margin Classifier.mp4 | Size: (10.06 MB)FileName :112 Support Vector classifiers.mp4 | Size: (55.67 MB)FileName :113 Limitations of Support Vector Classifiers.mp4 | Size: (10.65 MB)FileName :114 Kernel Based Support Vector Machines.mp4 | Size: (39.5 MB)FileName :115 Regression and Classification Models.mp4 | Size: (4.06 MB)FileName :116 Importing and preprocessing data in Python.mp4 | Size: (26.62 MB)FileName :117 Standardizing the data.mp4 | Size: (39.29 MB)FileName :118 SVM based Regression Model in Pytho.mp4 | Size: (71.96 MB)FileName :119 Classification model - Preprocessing.mp4 | Size: (48.78 MB)FileName :12 Outlier Treatment in Python.mp4 | Size: (74.03 MB)FileName :120 Classification model - Standardizing the data.mp4 | Size: (10.35 MB)FileName :121 SVM Based classification model.mp4 | Size: (66.24 MB)FileName :122 Hyper Parameter Tuning.mp4 | Size: (61.09 MB)FileName :123 Polynomial Kernel with Hyperparameter Tuning.mp4 | Size: (24.16 MB)FileName :124 Radial Kernel with Hyperparameter Tuning.mp4 | Size: (39.83 MB)FileName :125 Importing and preprocessing data in R.mp4 | Size: (53.5 MB)FileName :126 Classification SVM model using Linear Kernel.mp4 | Size: (139.78 MB)FileName :127 Hyperparameter Tuning for Linear Kernel.mp4 | Size: (61.15 MB)FileName :128 Polynomial Kernel with Hyperparameter Tuning.mp4 | Size: (83.18 MB)FileName :129 Radial Kernel with Hyperparameter Tuning.mp4 | Size: (56.78 MB)FileName :13 Outlier Treatment in R.mp4 | Size: (31.36 MB)FileName :130 SVM based Regression Model in R.mp4 | Size: (107.74 MB)FileName :14 Missing Value Imputation.mp4 | Size: (23.89 MB)FileName :15 Missing Value Imputation in Python.mp4 | Size: (24.69 MB)FileName :16 Missing Value imputation in R.mp4 | Size: (26.55 MB)FileName :17 Seasonality in Data.mp4 | Size: (16.52 MB)FileName :18 Bi-variate analysis and Variable transformation.mp4 | Size: (96.74 MB)FileName :19 Variable transformation and deletion in Python.mp4 | Size: (46.19 MB)FileName :2 Building a Machine Learning Model.mp4 | Size: (38.11 MB)FileName :20 Variable transformation in R.mp4 | Size: (56.94 MB)FileName :21 Non-usable variables.mp4 | Size: (18.61 MB)FileName :22 Dummy variable creation Handling qualitative data.mp4 | Size: (35.79 MB)FileName :23 Dummy variable creation in Python.mp4 | Size: (27.63 MB)FileName :24 Dummy variable creation in R.mp4 | Size: (46.42 MB)FileName :25 Correlation Analysis.mp4 | Size: (69.09 MB)FileName :26 Correlation Analysis in Python.mp4 | Size: (58.88 MB)FileName :27 Correlation Matrix in R.mp4 | Size: (86.21 MB)FileName :28 The Problem Statement.mp4 | Size: (9.5 MB)FileName :29 Basic Equations and Ordinary Least Squares (OLS) method.mp4 | Size: (41.78 MB)FileName :3 Gathering Business Knowledge.mp4 | Size: (20.24 MB)FileName :30 Assessing accuracy of predicted coefficients.mp4 | Size: (90.66 MB)FileName :31 Assessing Model Accuracy RSE and R squared.mp4 | Size: (41.92 MB)FileName :32 Simple Linear Regression in Python.mp4 | Size: (65.7 MB)FileName :33 Simple Linear Regression in R.mp4 | Size: (39.97 MB)FileName :34 Multiple Linear Regression.mp4 | Size: (33.11 MB)FileName :35 The F - statistic.mp4 | Size: (54.04 MB)FileName :36 Interpreting results of Categorical variables.mp4 | Size: (21.26 MB)FileName :37 Multiple Linear Regression in Python.mp4 | Size: (70.5 MB)FileName :38 Multiple Linear Regression in R.mp4 | Size: (63.53 MB)FileName :39 Test-train split.mp4 | Size: (40.41 MB)FileName :4 Data Exploration.mp4 | Size: (19.9 MB)FileName :40 Bias Variance trade-off.mp4 | Size: (23.88 MB)FileName :41 Test train split in Python.mp4 | Size: (45.27 MB)FileName :42 Test-Train Split in R.mp4 | Size: (75.61 MB)FileName :43 Regression models other than OLS.mp4 | Size: (15.36 MB)FileName :44 Subset selection techniques.mp4 | Size: (76.28 MB)FileName :45 SubShrinkage methods Ridge and Lassoset selection in R.mp4 | Size: (31.19 MB)FileName :46 Ridge regression and Lasso in Python.mp4 | Size: (132.2 MB)FileName :47 Heteroscedasticity.mp4 | Size: (14.25 MB)FileName :48 Ridge Regression and Lasso in R.mp4 | Size: (104.25 MB)FileName :49 importing the data into Python.mp4 | Size: (21.9 MB)FileName :5 Dataset & Data Dictionary.mp4 | Size: (74.89 MB)FileName :50 Importing the data into R.mp4 | Size: (13.72 MB)FileName :51 Three Classifiers and the Problem statement.mp4 | Size: (20.13 MB)FileName :52 Why can't we use Linear Regression.mp4 | Size: (15.63 MB)FileName :53 Logistic Regression.mp4 | Size: (31.17 MB)FileName :54 Training a Simple Logistic Model in Python.mp4 | Size: (47.67 MB)FileName :55 Training a Simple Logistic model in R.mp4 | Size: (16.11 MB)FileName :56 Result of Simple Logistic Regression.mp4 | Size: (25.93 MB)FileName :57 Logistic with multiple predictors.mp4 | Size: (7.92 MB)FileName :58 Training multiple predictor Logistic model in Python.mp4 | Size: (26.79 MB)FileName :59 Training multiple predictor Logistic model in R.mp4 | Size: (16.1 MB)FileName :6 Importing Data in Python.mp4 | Size: (28.14 MB)FileName :60 Confusion Matrix.mp4 | Size: (20.17 MB)FileName :61 Creating Confusion Matrix in Python.mp4 | Size: (53.73 MB)FileName :62 Evaluating performance of model.mp4 | Size: (34.27 MB)FileName :63 Evaluating model performance in Python.mp4 | Size: (9.13 MB)FileName :64 Predicting probabilities, assigning classes and making Confusion Matrix in R.mp4 | Size: (55.44 MB)FileName :65 Linear Discriminant Analysis.mp4 | Size: (38.88 MB)FileName :66 LDA in Python.mp4 | Size: (12.06 MB)FileName :67 Linear Discriminant Analysis in R.mp4 | Size: (74.82 MB)FileName :68 Test-Train Split.mp4 | Size: (37.33 MB)FileName :69 Test-Train Split in Python.mp4 | Size: (32.94 MB)FileName :7 Importing the dataset into R.mp4 | Size: (13.32 MB)FileName :70 Test-Train Split in R.mp4 | Size: (73.59 MB)FileName :71 K-Nearest Neighbors classifier.mp4 | Size: (73.38 MB)FileName :72 K-Nearest Neighbors in Python Part 1.mp4 | Size: (39.45 MB)FileName :73 K-Nearest Neighbors in Python Part 2.mp4 | Size: (46.18 MB)FileName :74 K-Nearest Neighbors in R.mp4 | Size: (64.36 MB)FileName :75 Understanding the results of classification models.mp4 | Size: (39.72 MB)FileName :76 Summary of the three models.mp4 | Size: (21.26 MB)FileName :77 Basics of Decision Trees.mp4 | Size: (40.25 MB)FileName :78 Understanding a Regression Tree.mp4 | Size: (41.22 MB)FileName :79 Stopping criteria for controlling tree growth.mp4 | Size: (13.07 MB)FileName :8 Univariate analysis and EDD.mp4 | Size: (23.51 MB)FileName :80 Importing the Data set into Python.mp4 | Size: (26.68 MB)FileName :81 Importing the Data set into R.mp4 | Size: (43.99 MB)FileName :82 Missing value treatment in Python.mp4 | Size: (18.65 MB)FileName :83 Dummy Variable creation in Python.mp4 | Size: (26.22 MB)FileName :84 Dependent- Independent Data split in Python.mp4 | Size: (15.34 MB)FileName :85 Test-Train split in Python.mp4 | Size: (24.76 MB)FileName :86 Splitting Data into Test and Train Set in R.mp4 | Size: (43.92 MB)FileName :87 Creating Decision tree in Python.mp4 | Size: (18.67 MB)FileName :88 Building a Regression Tree in R.mp4 | Size: (103.96 MB)FileName :89 Evaluating model performance in Python.mp4 | Size: (16.3 MB)FileName :9 EDD in Python.mp4 | Size: (65.95 MB)FileName :90 Plotting decision tree in Python.mp4 | Size: (21.54 MB)FileName :91 Pruning a tree.mp4 | Size: (17.36 MB)FileName :92 Pruning a tree in Python.mp4 | Size: (77.7 MB)FileName :93 Pruning a Tree in R.mp4 | Size: (83.91 MB)FileName :94 Ensemble technique 1 - Bagging.mp4 | Size: (27.47 MB)FileName :95 Ensemble technique 1 - Bagging in Python.mp4 | Size: (79.37 MB)FileName :96 Bagging in R.mp4 | Size: (59.29 MB)FileName :97 Ensemble technique 2 - Random Forests.mp4 | Size: (17.7 MB)FileName :98 Ensemble technique 2 - Random Forests in Python.mp4 | Size: (50 MB)FileName :99 Using Grid Search in Python.mp4 | Size: (84.35 MB)FileName :1 Introduction to Neural Networks and Course flow.mp4 | Size: (29.36 MB)FileName :2 Perceptron.mp4 | Size: (44.42 MB)FileName :3 Activation Functions.mp4 | Size: (34.37 MB)FileName :4 Python - Creating Perceptron model.mp4 | Size: (90.79 MB)FileName :5 Basic Terminologies.mp4 | Size: (40.73 MB)FileName :6 Gradient Descent.mp4 | Size: (60.9 MB)FileName :7 Back Propagation.mp4 | Size: (121.96 MB)FileName :8 Some Important Concepts.mp4 | Size: (61.03 MB)FileName :9 Hyperparameter.mp4 | Size: (44.67 MB)FileName :1 Keras and Tensorflow.mp4 | Size: (14.6 MB)FileName :10 Using Functional API for complex architectures.mp4 | Size: (96.4 MB)FileName :11 Saving - Restoring Models and Using Callbacks.mp4 | Size: (162.45 MB)FileName :12 Hyperparameter Tuning.mp4 | Size: (58.92 MB)FileName :2 Installing Tensorflow and Keras.mp4 | Size: (20.5 MB)FileName :3 Dataset for classification.mp4 | Size: (58.04 MB)FileName :4 Normalization and Test-Train split.mp4 | Size: (48.39 MB)FileName :5 Different ways to create ANN using Keras.mp4 | Size: (11 MB)FileName :6 Building the Neural Network using Keras.mp4 | Size: (82.93 MB)FileName :7 Compiling and Training the Neural Network model.mp4 | Size: (87.68 MB)FileName :8 Evaluating performance and Predicting using Keras.mp4 | Size: (74.43 MB)FileName :9 Building Neural Network for Regression Problem.mp4 | Size: (164.54 MB)FileName :1 Installing Keras and Tensorflow.mp4 | Size: (24.9 MB)FileName :2 Data Normalization and Test-Train Split.mp4 | Size: (124.64 MB)FileName :3 Building,Compiling and Training.mp4 | Size: (145.87 MB)FileName :4 Evaluating and Predicting.mp4 | Size: (111.6 MB)FileName :5 ANN with NeuralNets Package.mp4 | Size: (95.2 MB)FileName :6 Building Regression Model with Functional API.mp4 | Size: (146.55 MB)FileName :7 Complex Architectures using Functional API.mp4 | Size: (88.57 MB)FileName :8 Saving - Restoring Models and Using Callbacks.mp4 | Size: (242.47 MB)FileName :1 CNN Introduction.mp4 | Size: (56.12 MB)FileName :10 Comparison - Pooling vs Without Pooling in Python.mp4 | Size: (62.28 MB)FileName :11 CNN on MNIST Fashion Dataset - Model Architecture.mp4 | Size: (7.42 MB)FileName :12 Data Preprocessin.mp4 | Size: (75.93 MB)FileName :13 Creating Model Architecture.mp4 | Size: (82.31 MB)FileName :14 Compiling and training.mp4 | Size: (36.88 MB)FileName :15 Model Performance.mp4 | Size: (77.5 MB)FileName :16 Comparison - Pooling vs Without Pooling in R.mp4 | Size: (49.81 MB)FileName :2 Stride.mp4 | Size: (18.33 MB)FileName :3 Padding.mp4 | Size: (32.79 MB)FileName :4 Filters and Feature maps.mp4 | Size: (54.99 MB)FileName :5 Channels.mp4 | Size: (70.82 MB)FileName :6 PoolingLayer.mp4 | Size: (47.23 MB)FileName :7 CNN model in Python - Preprocessing.mp4 | Size: (42.87 MB)FileName :8 CNN model in Python - structure and Compile.mp4 | Size: (45.12 MB)FileName :9 CNN model in Python - 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