| 1. Adding & Joining Datasets.mp4 | 22.1 MB | ||
| 1. Adding & Joining Datasets.srt | 4.2 KB | ||
| 1. Adding Data.mp4 | 10.2 MB | ||
| 1. Adding Data.srt | 2.1 KB | ||
| 1. Adding Train & Test Data.mp4 | 5.6 MB | ||
| 1. Adding Train & Test Data.srt | 1.8 KB | ||
| 1. Adding Training Data.mp4 | 17.6 MB | ||
| 1. Adding Training Data.srt | 4.6 KB | ||
| 1. Getting Datasets for Practice.mp4 | 36.5 MB | ||
| 1. Getting Datasets for Practice.srt | 5 KB | ||
| 1. Navigating in SageMaker Canvas.mp4 | 10.1 MB | ||
| 1. Navigating in SageMaker Canvas.srt | 2.4 KB | ||
| 1. SageMaker Domain and User Setup.mp4 | 27.4 MB | ||
| 1. SageMaker Domain and User Setup.srt | 4.4 KB | ||
| 1. Versioning.mp4 | 23.7 MB | ||
| 1. Versioning.srt | 5.6 KB | ||
| 1. What is Amazon Web Services (AWS) .mp4 | 12.6 MB | ||
| 1. What is Amazon Web Services (AWS) .srt | 1.4 KB | ||
| 1. What is Machine Learning.mp4 | 39.2 MB | ||
| 1. What is Machine Learning.srt | 4.1 KB | ||
| 1. What is SageMaker and how it is used for Machine Learning.mp4 | 20.1 MB | ||
| 1. What is SageMaker and how it is used for Machine Learning.srt | 3.4 KB | ||
| 1. White Wine Quality Prediction.mp4 | 25.7 MB | ||
| 1. White Wine Quality Prediction.srt | 2.5 KB | ||
| 1.1 Bank Note Authentication - Test.csv | 49.4 KB | ||
| 1.1 Bright Data.html | 102.4 B | ||
| 1.1 Customer Churn Prediction - Test.csv | 68.5 KB | ||
| 1.1 Spam SMS Detection - Test.csv | 29.1 KB | ||
| 1.1 White Wine Quality Values Complete Data.csv | 258.2 KB | ||
| 1.1 Wine Quality - Red - Test.csv | 20.8 KB | ||
| 1.2 Bank Note Authentication - Train.csv | 24.5 KB | ||
| 1.2 Customer Churn Prediction - Train.csv | 378.6 KB | ||
| 1.2 Google Dataset Search.html | 102.4 B | ||
| 1.2 Spam SMS Detection - Train.csv | 103.4 KB | ||
| 1.2 Wine Quality - Red - Train(1).csv | 46.2 KB | ||
| 1.3 Kaggle.html | 102.4 B | ||
| 1.3 Wine Quality - Red - Train(2).csv | 22.5 KB | ||
| 1.4 Microsoft Research Open Data.html | 102.4 B | ||
| 1.5 Registry of Open Data on AWS.html | 102.4 B | ||
| 1.6 UCI Machine Learning Repository.html | 102.4 B | ||
| 2. Building Model.mp4 | 14.5 MB | ||
| 2. Building Model.srt | 3.2 KB | ||
| 2. Building and Using Model for Prediction.mp4 | 14.5 MB | ||
| 2. Building and Using Model for Prediction.srt | 3.1 KB | ||
| 2. Getting Help on SageMaker Canvas.mp4 | 26.1 MB | ||
| 2. Getting Help on SageMaker Canvas.srt | 4.8 KB | ||
| 2. Setup Data in S3 Buckets for use in SageMaker.mp4 | 19.9 MB | ||
| 2. Setup Data in S3 Buckets for use in SageMaker.srt | 3.4 KB | ||
| 2. Signing into AWS Console.mp4 | 15.7 MB | ||
| 2. Signing into AWS Console.srt | 2.1 KB | ||
| 2. What is SageMaker Canvas.mp4 | 9 MB | ||
| 2. What is SageMaker Canvas.srt | 3.8 KB | ||
| 3. Congratulations & Thankyou.mp4 | 18.1 MB | ||
| 3. Congratulations & Thankyou.srt | 1.4 KB | ||
| 3. Performing & Validating Predictions.mp4 | 19.2 MB | ||
| 3. Performing & Validating Predictions.srt | 4.8 KB | ||
| 3. Predict Single & Batch Dataset.mp4 | 35.3 MB | ||
| 3. Predict Single & Batch Dataset.srt | 8.5 KB | ||
| 3. Predicting Data and Validating Accuracy.mp4 | 8.4 MB | ||
| 3. Predicting Data and Validating Accuracy.srt | 2 KB | ||
| 3. Predicting Test Data.mp4 | 10.9 MB | ||
| 3. Predicting Test Data.srt | 2.9 KB | ||
| 4. Validating Accuracy of Batch Predictions.mp4 | 5.7 MB | ||
| 4. Validating Accuracy of Batch Predictions.srt | 2.9 KB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 70 total files | |||
No-Code Machine Learning Using Amazon AWS SageMaker Canvas
https://DevCourseWeb.com
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 26 lectures (1h 20m) | Size: 397.8 MB
Build your Machine Learning Model and get accurate predictions without writing any Code using AWS SageMaker Canvas
What you'll learn:
Machine Learning on Amazon's AWS Sagemaker Canvas without writing any Code
4 Live Projects with Sample Dataset
Training and Testing ML Models, Improving Accuracy
Basics of Machine Learning
Requirements
Basic Awareness of Machine Learning
No Coding Expertise needed.
No Advanced Machine Learning knowledge required
No heavy Software required
Description
This AWS SageMaker Canvas Course will help you to become a Machine Learning Expert and will enhance your skills by offering you comprehensive knowledge, and the required hands-on experience on this newly launched Cloud based ML tool, by solving real-time industry-based projects, without needing any complex coding expertise.
Top Reasons why you should learn AWS SageMaker Canvas :
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