| ned1313/Getting-Started-Terraform |
518 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
HCL |
| Exercise files for my Pluralsight course |
| rjurney/Agile_Data_Code_2 |
435 |
|
0 |
0 |
about 3 years ago |
0 |
|
7 |
mit |
Jupyter Notebook |
| Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition |
| AlessioCasco/AWS-CSA-2019-study-notes |
218 |
|
0 |
0 |
almost 5 years ago |
0 |
|
1 |
mit |
|
| My Study Notes for the AWS Certified Solutions Architect - Associate 2019 |
| ChandraLingam/AmazonSageMakerCourse |
210 |
|
0 |
0 |
over 2 years ago |
0 |
|
7 |
other |
Jupyter Notebook |
| In this AWS Machine Learning Specialty Course, You will gain first-hand experience on how to train, optimize, deploy, and integrate ML in AWS cloud. Learn how to use AWS Built-in SageMaker algorithms and AI, How to Bring Your Own Algorithm, Zero Downtime Model Deployment Options, How to Integrate and Invoke ML from your Application, Automated Hyperparameter Tuning |
| ned1313/Deep-Dive-Terraform |
180 |
|
0 |
0 |
over 2 years ago |
0 |
|
4 |
|
HCL |
| Exercise files for my Pluralsight course. |
| ACloudGuru-Resources/course-aws-certified-developer-associate |
163 |
|
0 |
0 |
over 2 years ago |
0 |
|
12 |
|
HTML |
| AWS Certified Developer Associate course |
| aws-samples/amazon-sagemaker-architecting-for-ml |
143 |
|
0 |
0 |
over 5 years ago |
0 |
|
4 |
mit |
Jupyter Notebook |
| Materials for a 2-day instructor led course on applying machine learning |
| ACloudGuru-Resources/Course_AWS_Certified_Machine_Learning |
129 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| stelligent/devops-essentials |
125 |
|
0 |
0 |
over 5 years ago |
0 |
|
9 |
mit |
HTML |
| Source code samples for DevOps Essentials on AWS Complete Video Course |
| linuxacademy/Content-AWS-Certified-Data-Analytics---Speciality |
97 |
|
0 |
0 |
over 3 years ago |
0 |
|
21 |
|
Jupyter Notebook |
| DAS-C01 ACG/LA by Brock Tubre and John Hanna |
