Modern Artificial Intelligence Masterclass Build Projects | B58642EBB82D2F21D3526BC5CF6636130F6937FC

Modern Artificial Intelligence Masterclass Build Projects

Name	Modern Artificial Intelligence Masterclass Build 6 Projects	DOWNLOAD Copy Link
Total Size	9.1 GB
Total Files	187
Last Seen	2024-10-06 23:40
Hash	B58642EBB82D2F21D3526BC5CF6636130F6937FC

/3. Emotion AI/
7. Task #6 - Understand Artificial Neural Networks (ANNs) Theory & Intuition.mp4	230.1 MB
1.1 Emotion AI Slides.pdf	3.2 MB
17. Task #16 - Understand Classifiers Key Performance Indicators (KPIs).srt	21.9 KB
9. Task #8 - Understand Convolutional Neural Networks and ResNets.mp4	133.2 MB
10. Task #9 - Build ResNet to Detect Key Facial Points.mp4	138.3 MB
1. Project Introduction and Welcome Message.srt	3.7 KB
5. Task #4 - Perform Images Augmentation.srt	27.6 KB
18. Task #17 - Assess Facial Expression Classifier Model.srt	21.6 KB
1. Project Introduction and Welcome Message.mp4	64.4 MB
2. Task #1 - Understand the Problem Statement & Business Case.mp4	124.7 MB
16. Task #15 - Build & Train a Facial Expression Classifier Model.srt	23.2 KB
1.2 Emotion AI Google Colab Notebook.html	0.1 KB
13. Task #12 - Import and Explore Facial Expressions (Emotions) Datasets.mp4	99.4 MB
15. Task #14 - Perform Image Augmentation.mp4	114.7 MB
11. Task #10 - Compile and Train Facial Key Points Detector Model.srt	11.8 KB
21. Task #20 - Serve Trained Model in TensorFlow 2.0 Serving.mp4	43.2 MB
17. Task #16 - Understand Classifiers Key Performance Indicators (KPIs).mp4	141.8 MB
16. Task #15 - Build & Train a Facial Expression Classifier Model.mp4	145.0 MB
8. Task #7 - Understand ANNs Training & Gradient Descent Algorithm.mp4	168.3 MB
20. Task #19 - Save Trained Model for Deployment.srt	15.0 KB
19. Task #18 - Make Predictions from Both Models 1. Key Facial Points & 2. Emotion.srt	11.6 KB
3. Task #2 - Import Libraries and Datasets.mp4	107.2 MB
14. Task #13 - Visualize Images for Facial Expression Detection.mp4	58.7 MB
9. Task #8 - Understand Convolutional Neural Networks and ResNets.srt	19.6 KB
2. Task #1 - Understand the Problem Statement & Business Case.srt	16.3 KB
20. Task #19 - Save Trained Model for Deployment.mp4	106.8 MB
10. Task #9 - Build ResNet to Detect Key Facial Points.srt	20.1 KB
12. Task #11 - Assess Trained ResNet Model Performance.srt	7.5 KB
15. Task #14 - Perform Image Augmentation.srt	20.5 KB
22. Task #21 - Deploy Both Models and Make Inference.mp4	92.8 MB
6. Task #5 - Perform Data Normalization and Scaling.srt	12.0 KB
4. Task #3 - Perform Image Visualizations.srt	15.2 KB
5. Task #4 - Perform Images Augmentation.mp4	148.7 MB
14. Task #13 - Visualize Images for Facial Expression Detection.srt	11.5 KB
18. Task #17 - Assess Facial Expression Classifier Model.mp4	109.6 MB
12. Task #11 - Assess Trained ResNet Model Performance.mp4	45.0 MB
13. Task #12 - Import and Explore Facial Expressions (Emotions) Datasets.srt	18.1 KB
21. Task #20 - Serve Trained Model in TensorFlow 2.0 Serving.srt	7.2 KB
6. Task #5 - Perform Data Normalization and Scaling.mp4	62.2 MB
19. Task #18 - Make Predictions from Both Models 1. Key Facial Points & 2. Emotion.mp4	63.0 MB
4. Task #3 - Perform Image Visualizations.mp4	91.6 MB
22. Task #21 - Deploy Both Models and Make Inference.srt	12.3 KB
3. Task #2 - Import Libraries and Datasets.srt	19.3 KB
8. Task #7 - Understand ANNs Training & Gradient Descent Algorithm.srt	27.7 KB
7. Task #6 - Understand Artificial Neural Networks (ANNs) Theory & Intuition.srt	31.9 KB
11. Task #10 - Compile and Train Facial Key Points Detector Model.mp4	71.4 MB
/4. AI in Healthcare/
1. Project Introduction and Welcome Message.srt	3.3 KB
1. Project Introduction and Welcome Message.mp4	60.8 MB
7. Task #6 - Train a Classifier Model To Detect Brain Tumors.mp4	211.1 MB
9. Task #8 - Understand ResUnet Segmentation Models Intuition.srt	21.3 KB
10. Task #9 - Build a Segmentation Model to Localize Brain Tumors.srt	22.1 KB
12. Task #11 - Assess Trained ResUNet Segmentation Model Performance.srt	19.2 KB
8. Task #7 - Assess Trained Classifier Model Performance.srt	14.1 KB
1.2 Healthcare AI Slides.pdf	4.6 MB
5. Task #4 - Understand the Intuition behind ResNet and CNNs.mp4	128.2 MB
4. Task #3 - Visualize and Explore Datasets.mp4	172.9 MB
5. Task #4 - Understand the Intuition behind ResNet and CNNs.srt	17.0 KB
3. Task #2 - Import Libraries and Datasets.mp4	112.3 MB
2. Task #1 - Understand the Problem Statement and Business Case.srt	24.6 KB
7. Task #6 - Train a Classifier Model To Detect Brain Tumors.srt	34.2 KB
11. Task #10 - Train ResUnet Segmentation Model.mp4	40.1 MB
1.1 AI in Healthcare Google Colab.html	0.1 KB
9. Task #8 - Understand ResUnet Segmentation Models Intuition.mp4	157.8 MB
10. Task #9 - Build a Segmentation Model to Localize Brain Tumors.mp4	143.4 MB
4. Task #3 - Visualize and Explore Datasets.srt	33.4 KB
11. Task #10 - Train ResUnet Segmentation Model.srt	6.1 KB
8. Task #7 - Assess Trained Classifier Model Performance.mp4	83.0 MB
2. Task #1 - Understand the Problem Statement and Business Case.mp4	184.5 MB
6. Task #5 - Understand Theory and Intuition Behind Transfer Learning.mp4	126.5 MB
3. Task #2 - Import Libraries and Datasets.srt	17.5 KB
6. Task #5 - Understand Theory and Intuition Behind Transfer Learning.srt	18.4 KB
12. Task #11 - Assess Trained ResUNet Segmentation Model Performance.mp4	134.9 MB
/2. Bonus Materials (Download now!)/
1. Link to Bonus Materials.html	1.7 KB
/6. AI In Business (Finance) & AutoML/
7. Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm.mp4	223.0 MB
5. Task #3 - Visualize and Explore Dataset.srt	32.0 KB
1. Project Introduction and Welcome Message.srt	3.1 KB
11. Task #9 - Understand XG-Boost in AWS SageMaker.mp4	81.5 MB
10. Task #8 - Perform Grid Search and Hyper-parameters Optimization.srt	10.8 KB
7. Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm.srt	33.3 KB
1. Project Introduction and Welcome Message.mp4	59.8 MB
9. Task #7 - Train XG-Boost Algorithm Using Scikit-Learn.mp4	74.9 MB
14. Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!).srt	22.6 KB
6. Task #4 - Clean Up the Data.mp4	58.3 MB
13. Task #11 - Deploy Model and Make Inference.mp4	113.1 MB
13. Task #11 - Deploy Model and Make Inference.srt	15.7 KB
2. Notes on Amazon Web Services (AWS).html	0.8 KB
1.2 UCI_Credit_Card.csv	2.9 MB
10. Task #8 - Perform Grid Search and Hyper-parameters Optimization.mp4	68.9 MB
3. Task #1 - Understand the Problem Statement & Business Case.srt	17.2 KB
1.3 AI in Finance.pdf	6.5 MB
5. Task #3 - Visualize and Explore Dataset.mp4	209.4 MB
1.1 AI In Business (Finance) & AutoML Google Colab.html	0.1 KB
1.4 AI in Finance - SageMaker AutoPilot.pdf	1.1 MB
6. Task #4 - Clean Up the Data.srt	9.3 KB
12. Task #10 - Train XG-Boost in AWS SageMaker.mp4	147.2 MB
8. Task #6 - Understand XG-Boost Algorithm Key Steps.mp4	215.5 MB
4. Task #2 - Import Libraries and Datasets.mp4	54.4 MB
12. Task #10 - Train XG-Boost in AWS SageMaker.srt	23.6 KB
14. Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!).mp4	128.8 MB
11. Task #9 - Understand XG-Boost in AWS SageMaker.srt	11.3 KB
8. Task #6 - Understand XG-Boost Algorithm Key Steps.srt	32.8 KB
4. Task #2 - Import Libraries and Datasets.srt	7.7 KB
9. Task #7 - Train XG-Boost Algorithm Using Scikit-Learn.srt	12.5 KB
3. Task #1 - Understand the Problem Statement & Business Case.mp4	110.6 MB
/
Download More Courses.html	0.2 KB
[TGx]Downloaded from torrentgalaxy.to.txt	0.6 KB
Important !! Course Resources Files.html	0.2 KB
/7. Creative AI/
1. Project Introduction and Welcome Message.srt	2.0 KB
1. Project Introduction and Welcome Message.mp4	38.9 MB
2. Task #1 - Understand the Problem Statement & Business Case.mp4	143.5 MB
10. Task #9 - Apply DeepDream Algorithm to Generate Images.mp4	70.1 MB
9. Task #8 - Implement Deep Dream Algorithm Part #2.mp4	126.6 MB
5. Task #4 - Run the Pre-trained Model and Explore Activations.srt	15.7 KB
1.3 Creative AI Google Colab.html	0.1 KB
3. Task #2 - Import Model with Pre-trained Weights.mp4	56.5 MB
4. Task #3 - Import and Merge Images.mp4	71.3 MB
11. Task #10 - Generate DeepDream Video.srt	11.1 KB
1.2 Creative AI.pdf	5.1 MB
6. Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm.mp4	204.5 MB
8. Task #7 - Implement Deep Dream Algorithm Part #1.srt	15.4 KB
9. Task #8 - Implement Deep Dream Algorithm Part #2.srt	18.1 KB
7. Task #6 - Understand The Gradient Operations in TF 2.0.srt	8.9 KB
2. Task #1 - Understand the Problem Statement & Business Case.srt	14.0 KB
11. Task #10 - Generate DeepDream Video.mp4	81.6 MB
7. Task #6 - Understand The Gradient Operations in TF 2.0.mp4	39.3 MB
10. Task #9 - Apply DeepDream Algorithm to Generate Images.srt	11.4 KB
5. Task #4 - Run the Pre-trained Model and Explore Activations.mp4	89.2 MB
8. Task #7 - Implement Deep Dream Algorithm Part #1.mp4	87.1 MB
4. Task #3 - Import and Merge Images.srt	14.7 KB
6. Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm.srt	31.4 KB
3. Task #2 - Import Model with Pre-trained Weights.srt	11.7 KB
/8. Explainable AI/
2. Introduction and Welcome Message.html	0.1 KB
1. Project Introduction and Welcome Message.srt	2.4 KB
1. Project Introduction and Welcome Message.mp4	41.5 MB
/9. Crash Course on AWS, S3, and SageMaker/
10. AWS SageMaker Studio Walk-through.srt	11.0 KB
7. AWS SageMaker Overview.mp4	67.8 MB
2. Key Machine Learning Components and AWS Tour.mp4	63.7 MB
8. AWS SageMaker Walk-through.srt	16.6 KB
5. EC2 and Identity and Access Management (IAM).mp4	113.5 MB
4. Amazon S3.mp4	116.8 MB
3. Regions and Availability Zones.mp4	55.5 MB
7. AWS SageMaker Overview.srt	13.7 KB
4. Amazon S3.srt	21.5 KB
9. AWS SageMaker Studio Overview.mp4	70.2 MB
3. Regions and Availability Zones.srt	9.0 KB
2. Key Machine Learning Components and AWS Tour.srt	14.0 KB
6. AWS Free Tier Account Setup and Overview.mp4	40.0 MB
1. What is AWS and Cloud Computing.mp4	71.4 MB
8. AWS SageMaker Walk-through.mp4	85.6 MB
11. AWS SageMaker Model Deployment.srt	15.5 KB
1. What is AWS and Cloud Computing.srt	12.1 KB
11. AWS SageMaker Model Deployment.mp4	116.2 MB
6. AWS Free Tier Account Setup and Overview.srt	8.8 KB
10. AWS SageMaker Studio Walk-through.mp4	54.0 MB
5. EC2 and Identity and Access Management (IAM).srt	19.1 KB
9. AWS SageMaker Studio Overview.srt	12.9 KB
/1. Introduction/
4. Get the Materials.html	0.4 KB
1. Introduction and Welcome Message.mp4	72.5 MB
3. Course Outline and Key Learning Outcomes.mp4	183.3 MB
3. Course Outline and Key Learning Outcomes.srt	24.9 KB
2. Introduction, Key Tips and Best Practices.srt	15.4 KB
2. Introduction, Key Tips and Best Practices.mp4	113.8 MB
1. Introduction and Welcome Message.srt	4.8 KB
/5. AI in Business (Marketing)/
6. Task #5 - Understand Theory and Intuition Behind K-Means Clustering Algorithm.srt	28.0 KB
2. Task #1 - Understand AI Applications in Marketing.srt	10.3 KB
5. Task #4 - Perform Exploratory Data Analysis (Part #2).srt	30.8 KB
1. Project Introduction and Welcome Message.srt	2.7 KB
8. Task #7 - Apply K-Means Clustering Algorithm.mp4	152.5 MB
1.3 AI in Marketing Slides.pdf	1.6 MB
8. Task #7 - Apply K-Means Clustering Algorithm.srt	25.0 KB
1. Project Introduction and Welcome Message.mp4	49.1 MB
1.1 AI in Business (Marketing) Google Colab.html	0.1 KB
10. Task #9 - Understand the Theory and Intuition Behind Auto-encoders.srt	12.8 KB
4. Task #3 - Perform Exploratory Data Analysis (Part #1).mp4	139.5 MB
7. Apply Elbow Method to Find the Optimal Number of Clusters.mp4	76.2 MB
9. Task #8 - Understand Intuition Behind Principal Component Analysis (PCA).srt	16.0 KB
3. Task #2 - Import Libraries and Datasets.mp4	111.7 MB
9. Task #8 - Understand Intuition Behind Principal Component Analysis (PCA).mp4	105.9 MB
5. Task #4 - Perform Exploratory Data Analysis (Part #2).mp4	191.8 MB
6. Task #5 - Understand Theory and Intuition Behind K-Means Clustering Algorithm.mp4	173.3 MB
7. Apply Elbow Method to Find the Optimal Number of Clusters.srt	13.2 KB
11. Task #10 - Apply Auto-encoders and Perform Clustering.mp4	141.9 MB
10. Task #9 - Understand the Theory and Intuition Behind Auto-encoders.mp4	87.1 MB
11. Task #10 - Apply Auto-encoders and Perform Clustering.srt	19.7 KB
3. Task #2 - Import Libraries and Datasets.srt	21.8 KB
4. Task #3 - Perform Exploratory Data Analysis (Part #1).srt	26.2 KB
2. Task #1 - Understand AI Applications in Marketing.mp4	77.3 MB
Total files 187