| 1. Creating a Hyperparameter Tuning Job; Bank Scenario.mp4 | 71.3 MB | ||
| 1. Creating a Hyperparameter Tuning Job; Bank Scenario.srt | 4.7 KB | ||
| 1. Deploying a Model.mp4 | 29.1 MB | ||
| 1. Deploying a Model.srt | 3.3 KB | ||
| 1. Introduction.mp4 | 51 MB | ||
| 1. Introduction.srt | 2.9 KB | ||
| 10. Automatic Model Tuning and Defining Metrics.mp4 | 88.2 MB | ||
| 10. Automatic Model Tuning and Defining Metrics.srt | 5.8 KB | ||
| 11. Automatic Model Tuning and Defining Metrics.html | 204.8 B | ||
| 12. Defining Hyperparameter Ranges and Scaling Types.mp4 | 39.9 MB | ||
| 12. Defining Hyperparameter Ranges and Scaling Types.srt | 2.7 KB | ||
| 13. Defining Hyperparameter Range and ScalingTypes.html | 204.8 B | ||
| 14. Creating an S3 bucket(2 Ways!).mp4 | 44.6 MB | ||
| 14. Creating an S3 bucket(2 Ways!).srt | 3.2 KB | ||
| 14.1 import com.amazonaws.AmazonServiceException; import com.amazonaws.SdkClientException; import com.amazonaws.auth.profile.ProfileCredentialsProvider; import com.amazonaws.regions.Regions; import com.amazonaws.services..pdf | 38 KB | ||
| 15. What is Sagemaker's Jumpstart.mp4 | 23.9 MB | ||
| 15. What is Sagemaker's Jumpstart.srt | 2.3 KB | ||
| 16. Performing Common Tasks on SageMaker's Studio.mp4 | 10.8 MB | ||
| 16. Performing Common Tasks on SageMaker's Studio.srt | 512 B | ||
| 17. Amazon's Behind the Scenes Code; Dedicated to all you coders out there!.mp4 | 39.4 MB | ||
| 17. Amazon's Behind the Scenes Code; Dedicated to all you coders out there!.srt | 3.4 KB | ||
| 2. Autopilot.mp4 | 16 MB | ||
| 2. Autopilot.srt | 3.4 KB | ||
| 2. Getting started on Sagemaker's Studio.mp4 | 39.8 MB | ||
| 2. Getting started on Sagemaker's Studio.srt | 3 KB | ||
| 2. Stopping Training Jobs Early.mp4 | 34.9 MB | ||
| 2. Stopping Training Jobs Early.srt | 2.3 KB | ||
| 3. First Assignment Automated ML.html | 204.8 B | ||
| 3. Stopping Training Jobs Early Quiz.html | 204.8 B | ||
| 3. What Sagemaker looks like and tools available!.mp4 | 6.4 MB | ||
| 3. What Sagemaker looks like and tools available!.srt | 1.2 KB | ||
| 4. Best Secrets for Hyperparameter Tuning.mp4 | 43.5 MB | ||
| 4. Best Secrets for Hyperparameter Tuning.srt | 3.2 KB | ||
| 4. Creating a Labeling Job.mp4 | 14.6 MB | ||
| 4. Creating a Labeling Job.srt | 3.1 KB | ||
| 4. Jupiter Notebooks on Sagemaker.mp4 | 33.1 MB | ||
| 4. Jupiter Notebooks on Sagemaker.srt | 2 KB | ||
| 5. Introduction to Data Wrangler.mp4 | 60.2 MB | ||
| 5. Introduction to Data Wrangler.srt | 3.6 KB | ||
| 5. Picking an algorithm on Sagemaker.mp4 | 34.8 MB | ||
| 5. Picking an algorithm on Sagemaker.srt | 2.2 KB | ||
| 5. Warm Start Hyperparameter Tuning Jobs.mp4 | 83.5 MB | ||
| 5. Warm Start Hyperparameter Tuning Jobs.srt | 5.5 KB | ||
| 6. Data Wrangler Demo.mp4 | 85.6 MB | ||
| 6. Data Wrangler Demo.srt | 5.1 KB | ||
| 6. Setting Hyperparameters.mp4 | 16.4 MB | ||
| 6. Setting Hyperparameters.srt | 1.6 KB | ||
| 6. Warm Start Hyperparameter Tuning Job Quiz.html | 204.8 B | ||
| 7. Amazon Augmented Al.mp4 | 79 MB | ||
| 7. Amazon Augmented Al.srt | 5.2 KB | ||
| 7. Creating a WarmStart Tuning Job low level Amazon Sageaker API for Python Boto 3.mp4 | 21.3 MB | ||
| 7. Creating a WarmStart Tuning Job low level Amazon Sageaker API for Python Boto 3.srt | 1.6 KB | ||
| 7. Teaching the computer with Training Data and Bias.mp4 | 29.4 MB | ||
| 7. Teaching the computer with Training Data and Bias.srt | 1.9 KB | ||
| 8. Creating a WarmStart Tuning Job using Amazon Sagemaker Python SDK.mp4 | 27.3 MB | ||
| 8. Creating a WarmStart Tuning Job using Amazon Sagemaker Python SDK.srt | 1.8 KB | ||
| 8. Training Data Quiz.html | 204.8 B | ||
| 9. 3 Types of testing on the model you can do!.mp4 | 29.4 MB | ||
| 9. 3 Types of testing on the model you can do!.srt | 1.6 KB | ||
| Bonus Resources.txt | 307.2 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 61 total files | |||
Amazon Sagemaker: Create and Deploy Machine Learning Today
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.02 GB | Duration: 58m
Learn Foundational Skills
What you'll learn
Know how to pick which of Sagemaker's algorithm to use.
Be able to create a Juypter notebook.
Be able to create an encryption key.
Utilize deep learning frameworks within Sagemaker.
Fix training data bias using Sagemaker's features.
Understand the purpose of Sagemaker's Clarify?
Choose whether to do online testing with live data or offline testing or do Machine Learning on a holdout set.
How to define a Hyperparameter range
Understand the different types of ScalingTypes you can use
Learn how to create an S3 bucket using 2 methods!
Be able to create a hyperparameter tuning job
Use best training jobs to create a model
Be able to stop a training job early and save time
Understand best practices for hyperparameter tuning jobs: what kind of range to use!
Understand the different WarmStart Hyperparameter tuning Jobs and what they do.
Understand IDENTICAL_DATA_AND_ALGORTITHM and TRANSFER_LEARNING
Use Sagemaker's Autopilot feature
Be able to deploy a model
Use JumpStart
Be able to use Data Wrangler
Import, Prepare, Analyze, and Transform data with Data Wrangler
Understand Augmented AI
Description
Are you looking to get into AWS Sagemaker, with no experience, and want to see if you like what Sagemaker is all about? Or do you know that Sagemaker is where you're future is headed but want to learn foundation skills needed for a career in machine learning?
But you have so many options out there for learning Sagemaker.
Why this course?
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 3.8 GB | freecoursewb | 2 weeks | 4 | 5 | |
| 691 MB | freecoursewb | 2 weeks | 0 | 0 | |
| 839.3 MB | freecoursewb | 2 months | 13 | 16 | |
|
Udemy - AWS Networking Masterclass - Amazon VPC and Hybrid Cloud 2026 Posted by
freecoursewb in Other
|
2.8 GB | freecoursewb | 2 months | 9 | 6 |
| 1.1 GB | freecoursewb | 3 months | 0 | 0 |
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