8.32 GB | 15min 52s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 Course Introduction and How to Download Code Files.mp4 (11.38 MB)
2 Google Colab Introduction.mp4 (17.34 MB)
4 Jupyter Notebook Introduction.mp4 (103.08 MB)
1 Python Introduction Part 1.mp4 (33.55 MB)
10 Seaborn Introduction Part 2.mp4 (59.71 MB)
2 Python Introduction Part 2.mp4 (37.82 MB)
3 Python Introduction Part 3.mp4 (34.65 MB)
4 Numpy Introduction Part 1.mp4 (40.09 MB)
5 Numpy Introduction Part 2.mp4 (36.29 MB)
6 Pandas Introduction.mp4 (49.56 MB)
7 Matplotlib Introduction Part 1.mp4 (64.76 MB)
8 Matplotlib Introduction Part 2.mp4 (70.1 MB)
9 Seaborn Introduction Part 1.mp4 (30.58 MB)
1 Classical Machine Learning Introduction.mp4 (31.97 MB)
10 Code Along in Python Part 1.mp4 (34.35 MB)
11 Code Along in Python Part 2.mp4 (59.15 MB)
12 Code Along in Python Part 3.mp4 (44.09 MB)
13 Code Along in Python Part 4.mp4 (66.67 MB)
2 Logistic Regression.mp4 (34.43 MB)
3 Support Vector Machine - SVM.mp4 (37.65 MB)
4 Decision Tree.mp4 (25.51 MB)
5 Random Forest.mp4 (17.48 MB)
6 L2 Regularization.mp4 (38.29 MB)
7 L1 Regularization.mp4 (18.74 MB)
8 Model Evaluation.mp4 (31.5 MB)
9 ROC-AUC Curve.mp4 (13.46 MB)
1 Machine Learning Process Introduction.mp4 (37.98 MB)
10 Deep Learning Tools.mp4 (31.78 MB)
11 MLops with AWS.mp4 (21.64 MB)
2 Types of Machine Learning.mp4 (19.28 MB)
3 Supervised Learning.mp4 (25.54 MB)
4 Unsupervised Learning.mp4 (43.23 MB)
5 Reinforcement Learning.mp4 (16.26 MB)
6 What is Deep Learning and ML.mp4 (30.2 MB)
7 What is Neural Network.mp4 (33.22 MB)
8 How Deep Learning Process Works.mp4 (23.95 MB)
9 Application of Deep Learning.mp4 (28.6 MB)
1 What is Neuron.mp4 (20.85 MB)
10 Data Visualization Part 2.mp4 (107.25 MB)
11 Data Preprocessing.mp4 (36.38 MB)
12 Import Neural Networks APIs.mp4 (37.05 MB)
13 How to Get Input Shape and Class Weights.mp4 (21.18 MB)
14 Neural Network Model Building.mp4 (60.86 MB)
15 Model Summary Explanation.mp4 (48.79 MB)
16 Model Training.mp4 (56.26 MB)
17 Model Evaluation.mp4 (16.1 MB)
18 Model Save and Load.mp4 (23.62 MB)
19 Prediction on Real-Life Data.mp4 (50.93 MB)
2 Multi-Layer Perceptron.mp4 (55.1 MB)
3 Shallow vs Deep Neural Networks.mp4 (13.85 MB)
4 Activation Function.mp4 (40.33 MB)
5 What is Back Propagation.mp4 (79.39 MB)
6 Optimizers in Deep Learning.mp4 (52.07 MB)
7 Steps to Build Neural Network.mp4 (64.07 MB)
8 Customer Churn Dataset Loading.mp4 (25.99 MB)
9 Data Visualization Part 1.mp4 (50.21 MB)
1 Introduction to Computer Vision with Deep Learning.mp4 (42.97 MB)
2 5 Steps of Computer Vision Model Building.mp4 (27.68 MB)
3 Fashion MNIST Dataset Download.mp4 (63.2 MB)
4 Fashion MNIST Dataset Analysis.mp4 (87.75 MB)
5 Train Test Split for Data.mp4 (25.81 MB)
6 Deep Neural Network Model Building.mp4 (36.53 MB)
7 Model Summary and Training.mp4 (64.97 MB)
8 Discovering Overfitting - Early Stopping.mp4 (77.53 MB)
9 Model Save and Load for Prediction.mp4 (44.68 MB)
1 What is Convolutional Neural Network.mp4 (64.2 MB)
10 LeNet-5 Architecture Explained.mp4 (71.12 MB)
11 AlexNet Architecture Explained.mp4 (98.71 MB)
12 GoogLeNet (Inception V1) Architecture Explained.mp4 (68.39 MB)
13 RestNet Architecture Explained.mp4 (56.84 MB)
14 MobileNet Architecture Explained.mp4 (121.33 MB)
15 EfficientNet Architecture Explained.mp4 (104.3 MB)
2 Working Principle of CNN.mp4 (80.21 MB)
3 Convolutional Filters.mp4 (114.04 MB)
4 Feature Maps.mp4 (66.88 MB)
5 Padding and Strides.mp4 (102.33 MB)
6 Pooling Layers.mp4 (86.51 MB)
7 Activation Function.mp4 (72.66 MB)
8 Dropout.mp4 (32.36 MB)
9 CNN Architectures Comparison.mp4 (55.56 MB)
1 Overview of Image Classification using CNNs.mp4 (44.05 MB)
10 CNN Parameter Calculations Part 2.mp4 (43.14 MB)
11 CNN Parameter Calculations Part 3.mp4 (61.42 MB)
12 Model Training.mp4 (58.94 MB)
13 Model Load and Save.mp4 (32.07 MB)
14 Image Class Prediction.mp4 (52.31 MB)
2 Introduction to TensorFlow Datasets (TFDS).mp4 (74.65 MB)
3 Download Humans or Horses Dataset Part 1.mp4 (56.15 MB)
4 Download Humans or Horses Dataset Part 2.mp4 (76.02 MB)
5 Use of Image Data Generator.mp4 (73.35 MB)
6 Data Display in Subplots Matrix.mp4 (89.21 MB)
7 CNN Introduction.mp4 (53.03 MB)
8 Building CNN Model.mp4 (60.67 MB)
9 CNN Parameter Calculation.mp4 (44.78 MB)
1 What is Overfitting.mp4 (42.76 MB)
10 TensorFlow TFDS and Cats vs Dogs Data Download.mp4 (42.39 MB)
11 Store Data in Local Directory.mp4 (53.06 MB)
12 Load Dataset for Baseline Classifier.mp4 (82.94 MB)
13 Building Baseline CNN Classifier.mp4 (41.61 MB)
14 How to Calculate Size of Output Layers of CNN and MaxPool.mp4 (61.31 MB)
15 How to Calculate Number of Parameters in CNN and FCN.mp4 (68.68 MB)
16 Model Training and Layers Analysis.mp4 (39.91 MB)
17 Model Training and Validation Accuracy Plot.mp4 (25.97 MB)
18 Building Dataset for Regularized CNN.mp4 (17.5 MB)
19 Regularized CNN Model Building and Training.mp4 (42.44 MB)
2 L1, L2 and Early Stopping Regularization.mp4 (44.8 MB)
20 Training Log Analysis.mp4 (25.54 MB)
21 Load Model and Do the Prediction.mp4 (83.4 MB)
22 CNN Model Visualization.mp4 (14.31 MB)
3 How Dropout and Batch Normalization Prevents Overfitting.mp4 (42.73 MB)
4 What is Data Augmentation Theory.mp4 (48.57 MB)
5 Sample Data Load with ImageDataGenerator for Augmentation.mp4 (71.05 MB)
6 Random Rotation Augmentation.mp4 (55.81 MB)
7 Random Shift Augmentation.mp4 (45.94 MB)
8 Other Types of Data Augmentation.mp4 (73.34 MB)
9 All Types of Augmentation at Once.mp4 (32.66 MB)
1 Transfer Learning Introduction.mp4 (57.42 MB)
10 Train Model with TFDS Data Without Saving Locally Part 2.mp4 (38.45 MB)
11 import VGG16 from Keras.mp4 (51.01 MB)
12 Data Augmentation for Training.mp4 (25.62 MB)
13 Make CNN Model with VGG16 Transfer Learning.mp4 (63.92 MB)
14 Model Training for Better Accuracy.mp4 (23.35 MB)
15 Train Any Model for Transfer Learning.mp4 (63.26 MB)
16 Save and Load Model with Class Names.mp4 (40.37 MB)
17 Online Prediction of Flowers Classes.mp4 (96.93 MB)
2 Load Flowers Dataset for Classification.mp4 (67.98 MB)
3 Download Flowers Data.mp4 (50 MB)
4 Flowers Data Visualization.mp4 (48.68 MB)
5 Preparing Data with Image Data Generator.mp4 (51.14 MB)
6 Baseline CNN Model Building.mp4 (46.36 MB)
7 How to Calculate Number of Parameters in CNN.mp4 (63.81 MB)
8 Baseline CNN Model Training.mp4 (46.34 MB)
9 Train Model with TFDS Data Without Saving Locally Part 1.mp4 (41.3 MB)
1 Introduction to NLP.mp4 (22.55 MB)
10 Pair Plot.mp4 (41.94 MB)
11 Train Test Split.mp4 (8.74 MB)
12 TF-IDF Vectorization.mp4 (34.71 MB)
13 Model Evaluation and Prediction on Real Data.mp4 (22.25 MB)
14 Model Load and Store.mp4 (22.06 MB)
2 What are Key NLP Techniques.mp4 (39.57 MB)
3 Overview of NLP Tools.mp4 (64.53 MB)
4 Common Challenges in NLP.mp4 (19.12 MB)
5 Bag of Words - The Simples Word Embedding Technique.mp4 (27.3 MB)
6 Term Frequency - Inverse Document Frequency (TF-IDF).mp4 (20.02 MB)
7 Load Spam Dataset.mp4 (18.55 MB)
8 Text Preprocessing.mp4 (45.77 MB)
9 Feature Engineering.mp4 (33.7 MB)
1 Tokenizers in Deep Learning.mp4 (59.19 MB)
10 1D Convolutional Model Building.mp4 (55.19 MB)
11 Training and Validation.mp4 (55.35 MB)
12 Model Saving and Loading and Prediction.mp4 (44.19 MB)
2 Padding in Deep Learning.mp4 (30.42 MB)
3 Keras Embeddings.mp4 (54.11 MB)
4 Tokenizer Coding.mp4 (32.23 MB)
5 Padding Coding.mp4 (41.44 MB)
6 IMDB Dataset Preparation.mp4 (71.79 MB)
7 Text Cleaning.mp4 (56.76 MB)
8 Text Length Plot.mp4 (20.28 MB)
9 Dataset Tokenization for Training.mp4 (32.02 MB)
1 What is RNN.mp4 (50.63 MB)
10 Model Building.mp4 (44.48 MB)
11 Model Training and Evaluation.mp4 (44.62 MB)
12 Bidirectional LSTM BiLSTM.mp4 (37.33 MB)
13 Model Loading and Saving.mp4 (58.27 MB)
2 Exploding and Vanishing Gradients in RNN.mp4 (39.09 MB)
3 Introduction to LSTM.mp4 (54.57 MB)
4 AG News Dataset Preparation Part 1.mp4 (23.26 MB)
5 AG News Dataset Preparation Part 2.mp4 (49.45 MB)
6 AG News Dataset Preparation Part 3.mp4 (55.03 MB)
7 Text Cleaning.mp4 (29.65 MB)
8 Tokenization Part 1.mp4 (27.44 MB)
9 Tokenization Part 2.mp4 (27.21 MB)
1 Time Series Data Preparation Introduction Theory.mp4 (43.36 MB)
2 Loading Tesla Stock Data.mp4 (43.21 MB)
3 Train Test Split for Stock Data.mp4 (32.06 MB)
4 Feature Normalization.mp4 (33.34 MB)
5 Dataset Windowing.mp4 (52.82 MB)
6 Creating LSTM Model for Time Series Data.mp4 (42.24 MB)
7 Model Evaluation and Correction.mp4 (70.93 MB)
8 Load and Save Model.mp4 (9.58 MB)
2 Google Colab Introduction.mp4 (17.34 MB)
4 Jupyter Notebook Introduction.mp4 (103.08 MB)
1 Python Introduction Part 1.mp4 (33.55 MB)
10 Seaborn Introduction Part 2.mp4 (59.71 MB)
2 Python Introduction Part 2.mp4 (37.82 MB)
3 Python Introduction Part 3.mp4 (34.65 MB)
4 Numpy Introduction Part 1.mp4 (40.09 MB)
5 Numpy Introduction Part 2.mp4 (36.29 MB)
6 Pandas Introduction.mp4 (49.56 MB)
7 Matplotlib Introduction Part 1.mp4 (64.76 MB)
8 Matplotlib Introduction Part 2.mp4 (70.1 MB)
9 Seaborn Introduction Part 1.mp4 (30.58 MB)
1 Classical Machine Learning Introduction.mp4 (31.97 MB)
10 Code Along in Python Part 1.mp4 (34.35 MB)
11 Code Along in Python Part 2.mp4 (59.15 MB)
12 Code Along in Python Part 3.mp4 (44.09 MB)
13 Code Along in Python Part 4.mp4 (66.67 MB)
2 Logistic Regression.mp4 (34.43 MB)
3 Support Vector Machine - SVM.mp4 (37.65 MB)
4 Decision Tree.mp4 (25.51 MB)
5 Random Forest.mp4 (17.48 MB)
6 L2 Regularization.mp4 (38.29 MB)
7 L1 Regularization.mp4 (18.74 MB)
8 Model Evaluation.mp4 (31.5 MB)
9 ROC-AUC Curve.mp4 (13.46 MB)
1 Machine Learning Process Introduction.mp4 (37.98 MB)
10 Deep Learning Tools.mp4 (31.78 MB)
11 MLops with AWS.mp4 (21.64 MB)
2 Types of Machine Learning.mp4 (19.28 MB)
3 Supervised Learning.mp4 (25.54 MB)
4 Unsupervised Learning.mp4 (43.23 MB)
5 Reinforcement Learning.mp4 (16.26 MB)
6 What is Deep Learning and ML.mp4 (30.2 MB)
7 What is Neural Network.mp4 (33.22 MB)
8 How Deep Learning Process Works.mp4 (23.95 MB)
9 Application of Deep Learning.mp4 (28.6 MB)
1 What is Neuron.mp4 (20.85 MB)
10 Data Visualization Part 2.mp4 (107.25 MB)
11 Data Preprocessing.mp4 (36.38 MB)
12 Import Neural Networks APIs.mp4 (37.05 MB)
13 How to Get Input Shape and Class Weights.mp4 (21.18 MB)
14 Neural Network Model Building.mp4 (60.86 MB)
15 Model Summary Explanation.mp4 (48.79 MB)
16 Model Training.mp4 (56.26 MB)
17 Model Evaluation.mp4 (16.1 MB)
18 Model Save and Load.mp4 (23.62 MB)
19 Prediction on Real-Life Data.mp4 (50.93 MB)
2 Multi-Layer Perceptron.mp4 (55.1 MB)
3 Shallow vs Deep Neural Networks.mp4 (13.85 MB)
4 Activation Function.mp4 (40.33 MB)
5 What is Back Propagation.mp4 (79.39 MB)
6 Optimizers in Deep Learning.mp4 (52.07 MB)
7 Steps to Build Neural Network.mp4 (64.07 MB)
8 Customer Churn Dataset Loading.mp4 (25.99 MB)
9 Data Visualization Part 1.mp4 (50.21 MB)
1 Introduction to Computer Vision with Deep Learning.mp4 (42.97 MB)
2 5 Steps of Computer Vision Model Building.mp4 (27.68 MB)
3 Fashion MNIST Dataset Download.mp4 (63.2 MB)
4 Fashion MNIST Dataset Analysis.mp4 (87.75 MB)
5 Train Test Split for Data.mp4 (25.81 MB)
6 Deep Neural Network Model Building.mp4 (36.53 MB)
7 Model Summary and Training.mp4 (64.97 MB)
8 Discovering Overfitting - Early Stopping.mp4 (77.53 MB)
9 Model Save and Load for Prediction.mp4 (44.68 MB)
1 What is Convolutional Neural Network.mp4 (64.2 MB)
10 LeNet-5 Architecture Explained.mp4 (71.12 MB)
11 AlexNet Architecture Explained.mp4 (98.71 MB)
12 GoogLeNet (Inception V1) Architecture Explained.mp4 (68.39 MB)
13 RestNet Architecture Explained.mp4 (56.84 MB)
14 MobileNet Architecture Explained.mp4 (121.33 MB)
15 EfficientNet Architecture Explained.mp4 (104.3 MB)
2 Working Principle of CNN.mp4 (80.21 MB)
3 Convolutional Filters.mp4 (114.04 MB)
4 Feature Maps.mp4 (66.88 MB)
5 Padding and Strides.mp4 (102.33 MB)
6 Pooling Layers.mp4 (86.51 MB)
7 Activation Function.mp4 (72.66 MB)
8 Dropout.mp4 (32.36 MB)
9 CNN Architectures Comparison.mp4 (55.56 MB)
1 Overview of Image Classification using CNNs.mp4 (44.05 MB)
10 CNN Parameter Calculations Part 2.mp4 (43.14 MB)
11 CNN Parameter Calculations Part 3.mp4 (61.42 MB)
12 Model Training.mp4 (58.94 MB)
13 Model Load and Save.mp4 (32.07 MB)
14 Image Class Prediction.mp4 (52.31 MB)
2 Introduction to TensorFlow Datasets (TFDS).mp4 (74.65 MB)
3 Download Humans or Horses Dataset Part 1.mp4 (56.15 MB)
4 Download Humans or Horses Dataset Part 2.mp4 (76.02 MB)
5 Use of Image Data Generator.mp4 (73.35 MB)
6 Data Display in Subplots Matrix.mp4 (89.21 MB)
7 CNN Introduction.mp4 (53.03 MB)
8 Building CNN Model.mp4 (60.67 MB)
9 CNN Parameter Calculation.mp4 (44.78 MB)
1 What is Overfitting.mp4 (42.76 MB)
10 TensorFlow TFDS and Cats vs Dogs Data Download.mp4 (42.39 MB)
11 Store Data in Local Directory.mp4 (53.06 MB)
12 Load Dataset for Baseline Classifier.mp4 (82.94 MB)
13 Building Baseline CNN Classifier.mp4 (41.61 MB)
14 How to Calculate Size of Output Layers of CNN and MaxPool.mp4 (61.31 MB)
15 How to Calculate Number of Parameters in CNN and FCN.mp4 (68.68 MB)
16 Model Training and Layers Analysis.mp4 (39.91 MB)
17 Model Training and Validation Accuracy Plot.mp4 (25.97 MB)
18 Building Dataset for Regularized CNN.mp4 (17.5 MB)
19 Regularized CNN Model Building and Training.mp4 (42.44 MB)
2 L1, L2 and Early Stopping Regularization.mp4 (44.8 MB)
20 Training Log Analysis.mp4 (25.54 MB)
21 Load Model and Do the Prediction.mp4 (83.4 MB)
22 CNN Model Visualization.mp4 (14.31 MB)
3 How Dropout and Batch Normalization Prevents Overfitting.mp4 (42.73 MB)
4 What is Data Augmentation Theory.mp4 (48.57 MB)
5 Sample Data Load with ImageDataGenerator for Augmentation.mp4 (71.05 MB)
6 Random Rotation Augmentation.mp4 (55.81 MB)
7 Random Shift Augmentation.mp4 (45.94 MB)
8 Other Types of Data Augmentation.mp4 (73.34 MB)
9 All Types of Augmentation at Once.mp4 (32.66 MB)
1 Transfer Learning Introduction.mp4 (57.42 MB)
10 Train Model with TFDS Data Without Saving Locally Part 2.mp4 (38.45 MB)
11 import VGG16 from Keras.mp4 (51.01 MB)
12 Data Augmentation for Training.mp4 (25.62 MB)
13 Make CNN Model with VGG16 Transfer Learning.mp4 (63.92 MB)
14 Model Training for Better Accuracy.mp4 (23.35 MB)
15 Train Any Model for Transfer Learning.mp4 (63.26 MB)
16 Save and Load Model with Class Names.mp4 (40.37 MB)
17 Online Prediction of Flowers Classes.mp4 (96.93 MB)
2 Load Flowers Dataset for Classification.mp4 (67.98 MB)
3 Download Flowers Data.mp4 (50 MB)
4 Flowers Data Visualization.mp4 (48.68 MB)
5 Preparing Data with Image Data Generator.mp4 (51.14 MB)
6 Baseline CNN Model Building.mp4 (46.36 MB)
7 How to Calculate Number of Parameters in CNN.mp4 (63.81 MB)
8 Baseline CNN Model Training.mp4 (46.34 MB)
9 Train Model with TFDS Data Without Saving Locally Part 1.mp4 (41.3 MB)
1 Introduction to NLP.mp4 (22.55 MB)
10 Pair Plot.mp4 (41.94 MB)
11 Train Test Split.mp4 (8.74 MB)
12 TF-IDF Vectorization.mp4 (34.71 MB)
13 Model Evaluation and Prediction on Real Data.mp4 (22.25 MB)
14 Model Load and Store.mp4 (22.06 MB)
2 What are Key NLP Techniques.mp4 (39.57 MB)
3 Overview of NLP Tools.mp4 (64.53 MB)
4 Common Challenges in NLP.mp4 (19.12 MB)
5 Bag of Words - The Simples Word Embedding Technique.mp4 (27.3 MB)
6 Term Frequency - Inverse Document Frequency (TF-IDF).mp4 (20.02 MB)
7 Load Spam Dataset.mp4 (18.55 MB)
8 Text Preprocessing.mp4 (45.77 MB)
9 Feature Engineering.mp4 (33.7 MB)
1 Tokenizers in Deep Learning.mp4 (59.19 MB)
10 1D Convolutional Model Building.mp4 (55.19 MB)
11 Training and Validation.mp4 (55.35 MB)
12 Model Saving and Loading and Prediction.mp4 (44.19 MB)
2 Padding in Deep Learning.mp4 (30.42 MB)
3 Keras Embeddings.mp4 (54.11 MB)
4 Tokenizer Coding.mp4 (32.23 MB)
5 Padding Coding.mp4 (41.44 MB)
6 IMDB Dataset Preparation.mp4 (71.79 MB)
7 Text Cleaning.mp4 (56.76 MB)
8 Text Length Plot.mp4 (20.28 MB)
9 Dataset Tokenization for Training.mp4 (32.02 MB)
1 What is RNN.mp4 (50.63 MB)
10 Model Building.mp4 (44.48 MB)
11 Model Training and Evaluation.mp4 (44.62 MB)
12 Bidirectional LSTM BiLSTM.mp4 (37.33 MB)
13 Model Loading and Saving.mp4 (58.27 MB)
2 Exploding and Vanishing Gradients in RNN.mp4 (39.09 MB)
3 Introduction to LSTM.mp4 (54.57 MB)
4 AG News Dataset Preparation Part 1.mp4 (23.26 MB)
5 AG News Dataset Preparation Part 2.mp4 (49.45 MB)
6 AG News Dataset Preparation Part 3.mp4 (55.03 MB)
7 Text Cleaning.mp4 (29.65 MB)
8 Tokenization Part 1.mp4 (27.44 MB)
9 Tokenization Part 2.mp4 (27.21 MB)
1 Time Series Data Preparation Introduction Theory.mp4 (43.36 MB)
2 Loading Tesla Stock Data.mp4 (43.21 MB)
3 Train Test Split for Stock Data.mp4 (32.06 MB)
4 Feature Normalization.mp4 (33.34 MB)
5 Dataset Windowing.mp4 (52.82 MB)
6 Creating LSTM Model for Time Series Data.mp4 (42.24 MB)
7 Model Evaluation and Correction.mp4 (70.93 MB)
8 Load and Save Model.mp4 (9.58 MB)
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