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Modern Artificial Intelligence Masterclass Build 6 Projects
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3. Emotion AI (Size: 8.45 GB) (Files: 187)
3. Emotion AI
7. Task #6 - Understand Artificial Neural Networks (ANNs) Theory & Intuition.mp4
1.1 Emotion AI Slides.pdf
17. Task #16 - Understand Classifiers Key Performance Indicators (KPIs).srt
9. Task #8 - Understand Convolutional Neural Networks and ResNets.mp4
10. Task #9 - Build ResNet to Detect Key Facial Points.mp4
1. Project Introduction and Welcome Message.srt
5. Task #4 - Perform Images Augmentation.srt
18. Task #17 - Assess Facial Expression Classifier Model.srt
1. Project Introduction and Welcome Message.mp4
2. Task #1 - Understand the Problem Statement & Business Case.mp4
16. Task #15 - Build & Train a Facial Expression Classifier Model.srt
1.2 Emotion AI Google Colab Notebook.html
13. Task #12 - Import and Explore Facial Expressions (Emotions) Datasets.mp4
15. Task #14 - Perform Image Augmentation.mp4
11. Task #10 - Compile and Train Facial Key Points Detector Model.srt
21. Task #20 - Serve Trained Model in TensorFlow 2.0 Serving.mp4
17. Task #16 - Understand Classifiers Key Performance Indicators (KPIs).mp4
16. Task #15 - Build & Train a Facial Expression Classifier Model.mp4
8. Task #7 - Understand ANNs Training & Gradient Descent Algorithm.mp4
20. Task #19 - Save Trained Model for Deployment.srt
19. Task #18 - Make Predictions from Both Models 1. Key Facial Points & 2. Emotion.srt
3. Task #2 - Import Libraries and Datasets.mp4
14. Task #13 - Visualize Images for Facial Expression Detection.mp4
9. Task #8 - Understand Convolutional Neural Networks and ResNets.srt
2. Task #1 - Understand the Problem Statement & Business Case.srt
20. Task #19 - Save Trained Model for Deployment.mp4
10. Task #9 - Build ResNet to Detect Key Facial Points.srt
12. Task #11 - Assess Trained ResNet Model Performance.srt
15. Task #14 - Perform Image Augmentation.srt
22. Task #21 - Deploy Both Models and Make Inference.mp4
6. Task #5 - Perform Data Normalization and Scaling.srt
4. Task #3 - Perform Image Visualizations.srt
5. Task #4 - Perform Images Augmentation.mp4
14. Task #13 - Visualize Images for Facial Expression Detection.srt
18. Task #17 - Assess Facial Expression Classifier Model.mp4
12. Task #11 - Assess Trained ResNet Model Performance.mp4
13. Task #12 - Import and Explore Facial Expressions (Emotions) Datasets.srt
21. Task #20 - Serve Trained Model in TensorFlow 2.0 Serving.srt
6. Task #5 - Perform Data Normalization and Scaling.mp4
19. Task #18 - Make Predictions from Both Models 1. Key Facial Points & 2. Emotion.mp4
4. Task #3 - Perform Image Visualizations.mp4
22. Task #21 - Deploy Both Models and Make Inference.srt
3. Task #2 - Import Libraries and Datasets.srt
8. Task #7 - Understand ANNs Training & Gradient Descent Algorithm.srt
7. Task #6 - Understand Artificial Neural Networks (ANNs) Theory & Intuition.srt
11. Task #10 - Compile and Train Facial Key Points Detector Model.mp4
4. AI in Healthcare
1. Project Introduction and Welcome Message.srt
1. Project Introduction and Welcome Message.mp4
7. Task #6 - Train a Classifier Model To Detect Brain Tumors.mp4
9. Task #8 - Understand ResUnet Segmentation Models Intuition.srt
10. Task #9 - Build a Segmentation Model to Localize Brain Tumors.srt
12. Task #11 - Assess Trained ResUNet Segmentation Model Performance.srt
8. Task #7 - Assess Trained Classifier Model Performance.srt
1.2 Healthcare AI Slides.pdf
5. Task #4 - Understand the Intuition behind ResNet and CNNs.mp4
4. Task #3 - Visualize and Explore Datasets.mp4
5. Task #4 - Understand the Intuition behind ResNet and CNNs.srt
3. Task #2 - Import Libraries and Datasets.mp4
2. Task #1 - Understand the Problem Statement and Business Case.srt
7. Task #6 - Train a Classifier Model To Detect Brain Tumors.srt
11. Task #10 - Train ResUnet Segmentation Model.mp4
1.1 AI in Healthcare Google Colab.html
9. Task #8 - Understand ResUnet Segmentation Models Intuition.mp4
10. Task #9 - Build a Segmentation Model to Localize Brain Tumors.mp4
4. Task #3 - Visualize and Explore Datasets.srt
11. Task #10 - Train ResUnet Segmentation Model.srt
8. Task #7 - Assess Trained Classifier Model Performance.mp4
2. Task #1 - Understand the Problem Statement and Business Case.mp4
6. Task #5 - Understand Theory and Intuition Behind Transfer Learning.mp4
3. Task #2 - Import Libraries and Datasets.srt
6. Task #5 - Understand Theory and Intuition Behind Transfer Learning.srt
12. Task #11 - Assess Trained ResUNet Segmentation Model Performance.mp4
2. Bonus Materials (Download now!)
1. Link to Bonus Materials.html
6. AI In Business (Finance) & AutoML
7. Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm.mp4
5. Task #3 - Visualize and Explore Dataset.srt
1. Project Introduction and Welcome Message.srt
11. Task #9 - Understand XG-Boost in AWS SageMaker.mp4
10. Task #8 - Perform Grid Search and Hyper-parameters Optimization.srt
7. Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm.srt
1. Project Introduction and Welcome Message.mp4
9. Task #7 - Train XG-Boost Algorithm Using Scikit-Learn.mp4
14. Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!).srt
6. Task #4 - Clean Up the Data.mp4
13. Task #11 - Deploy Model and Make Inference.mp4
13. Task #11 - Deploy Model and Make Inference.srt
2. Notes on Amazon Web Services (AWS).html
1.2 UCI_Credit_Card.csv
10. Task #8 - Perform Grid Search and Hyper-parameters Optimization.mp4
3. Task #1 - Understand the Problem Statement & Business Case.srt
1.3 AI in Finance.pdf
5. Task #3 - Visualize and Explore Dataset.mp4
1.1 AI In Business (Finance) & AutoML Google Colab.html
1.4 AI in Finance - SageMaker AutoPilot.pdf
6. Task #4 - Clean Up the Data.srt
12. Task #10 - Train XG-Boost in AWS SageMaker.mp4
8. Task #6 - Understand XG-Boost Algorithm Key Steps.mp4
4. Task #2 - Import Libraries and Datasets.mp4
12. Task #10 - Train XG-Boost in AWS SageMaker.srt
14. Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!).mp4
11. Task #9 - Understand XG-Boost in AWS SageMaker.srt
8. Task #6 - Understand XG-Boost Algorithm Key Steps.srt
4. Task #2 - Import Libraries and Datasets.srt
9. Task #7 - Train XG-Boost Algorithm Using Scikit-Learn.srt
3. Task #1 - Understand the Problem Statement & Business Case.mp4
Download More Courses.html
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7. Creative AI
1. Project Introduction and Welcome Message.srt
1. Project Introduction and Welcome Message.mp4
2. Task #1 - Understand the Problem Statement & Business Case.mp4
10. Task #9 - Apply DeepDream Algorithm to Generate Images.mp4
9. Task #8 - Implement Deep Dream Algorithm Part #2.mp4
5. Task #4 - Run the Pre-trained Model and Explore Activations.srt
1.3 Creative AI Google Colab.html
3. Task #2 - Import Model with Pre-trained Weights.mp4
4. Task #3 - Import and Merge Images.mp4
11. Task #10 - Generate DeepDream Video.srt
1.2 Creative AI.pdf
6. Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm.mp4
8. Task #7 - Implement Deep Dream Algorithm Part #1.srt
9. Task #8 - Implement Deep Dream Algorithm Part #2.srt
7. Task #6 - Understand The Gradient Operations in TF 2.0.srt
2. Task #1 - Understand the Problem Statement & Business Case.srt
11. Task #10 - Generate DeepDream Video.mp4
7. Task #6 - Understand The Gradient Operations in TF 2.0.mp4
10. Task #9 - Apply DeepDream Algorithm to Generate Images.srt
5. Task #4 - Run the Pre-trained Model and Explore Activations.mp4
8. Task #7 - Implement Deep Dream Algorithm Part #1.mp4
4. Task #3 - Import and Merge Images.srt
6. Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm.srt
3. Task #2 - Import Model with Pre-trained Weights.srt
8. Explainable AI
2. Introduction and Welcome Message.html
1. Project Introduction and Welcome Message.srt
1. Project Introduction and Welcome Message.mp4
9. Crash Course on AWS, S3, and SageMaker
10. AWS SageMaker Studio Walk-through.srt
7. AWS SageMaker Overview.mp4
2. Key Machine Learning Components and AWS Tour.mp4
8. AWS SageMaker Walk-through.srt
5. EC2 and Identity and Access Management (IAM).mp4
4. Amazon S3.mp4
3. Regions and Availability Zones.mp4
7. AWS SageMaker Overview.srt
4. Amazon S3.srt
9. AWS SageMaker Studio Overview.mp4
3. Regions and Availability Zones.srt
2. Key Machine Learning Components and AWS Tour.srt
6. AWS Free Tier Account Setup and Overview.mp4
1. What is AWS and Cloud Computing.mp4
8. AWS SageMaker Walk-through.mp4
11. AWS SageMaker Model Deployment.srt
1. What is AWS and Cloud Computing.srt
11. AWS SageMaker Model Deployment.mp4
6. AWS Free Tier Account Setup and Overview.srt
10. AWS SageMaker Studio Walk-through.mp4
5. EC2 and Identity and Access Management (IAM).srt
9. AWS SageMaker Studio Overview.srt
1. Introduction
4. Get the Materials.html
1. Introduction and Welcome Message.mp4
3. Course Outline and Key Learning Outcomes.mp4
3. Course Outline and Key Learning Outcomes.srt
2. Introduction, Key Tips and Best Practices.srt
2. Introduction, Key Tips and Best Practices.mp4
1. Introduction and Welcome Message.srt
Important !! Course Resources Files.html
5. AI in Business (Marketing)
6. Task #5 - Understand Theory and Intuition Behind K-Means Clustering Algorithm.srt
2. Task #1 - Understand AI Applications in Marketing.srt
5. Task #4 - Perform Exploratory Data Analysis (Part #2).srt
1. Project Introduction and Welcome Message.srt
8. Task #7 - Apply K-Means Clustering Algorithm.mp4
1.3 AI in Marketing Slides.pdf
8. Task #7 - Apply K-Means Clustering Algorithm.srt
1. Project Introduction and Welcome Message.mp4
1.1 AI in Business (Marketing) Google Colab.html
10. Task #9 - Understand the Theory and Intuition Behind Auto-encoders.srt
4. Task #3 - Perform Exploratory Data Analysis (Part #1).mp4
7. Apply Elbow Method to Find the Optimal Number of Clusters.mp4
9. Task #8 - Understand Intuition Behind Principal Component Analysis (PCA).srt
3. Task #2 - Import Libraries and Datasets.mp4
9. Task #8 - Understand Intuition Behind Principal Component Analysis (PCA).mp4
5. Task #4 - Perform Exploratory Data Analysis (Part #2).mp4
6. Task #5 - Understand Theory and Intuition Behind K-Means Clustering Algorithm.mp4
7. Apply Elbow Method to Find the Optimal Number of Clusters.srt
11. Task #10 - Apply Auto-encoders and Perform Clustering.mp4
10. Task #9 - Understand the Theory and Intuition Behind Auto-encoders.mp4
11. Task #10 - Apply Auto-encoders and Perform Clustering.srt
3. Task #2 - Import Libraries and Datasets.srt
4. Task #3 - Perform Exploratory Data Analysis (Part #1).srt
2. Task #1 - Understand AI Applications in Marketing.mp4
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