AWS SageMaker Complete Course| PyTorch & Tensorflow in NLP paid course free. You will Build DL/ML model in Sklearn,Tensorflow/Keras & PyTorch. How to bring docker container&Algorithm from local to Sagemaker.
- What is SageMaker and Why it is required
- SageMaker Architechure
- Model Building using existing Docker Image in SageMaker
- Model Building using existing algorithm in SageMaker
- Model Building using SageMaker Pre-built algorithms
- Model Building in Tensorflow/Keras
- Model Building in Pytorch
- How to deploy the models in SageMaker
- How to make predictions from Endpoints
- Create complete End-to End machine learning Pipeline Workflow
- Real time example of NLP
- How to schedule the SageMaker notebook for Retraining
- How to Build ,deploy and schedule the Model
AWS SageMaker Complete Course| PyTorch & Tensorflow in NLP Course Requirements
- Free or paid subscription to AWS is required. It may ask for Phone and/or Credit Card for verification
- Python Basic knowledge
AWS SageMaker Complete Course| PyTorch & Tensorflow in NLP Course Description
This course is finished aide of AWS SageMaker wherein understudy will figure out how to fabricate, convey SageMaker models by tenderizing on-premises docker compartment and incorporate it to SageMaker. Course will likewise do deep drive on the most proficient method to acquire your own calculations AWS SageMaker Environment. Course will likewise disclose how to utilize pre-constructed improved SageMaker Algorithm.
Course will likewise do deep drive how to make pipeline and work process so model could be retrained and planned naturally.
This course will give you reasonable thoughts of how to assemble Transformer system in Keras for multi class grouping use cases. Another method of settling multi class characterization by utilizing pre-prepared model like Bert .
Both the Deep learning model later embodied in Docker in nearby machine and afterward push back to AWS ECR storehouse.
This course offers:
What is SageMaker and why it is required
SageMaker Machine Learning lifecycle
SageMaker training techniques:
Bring your own docker container from on premise to SageMaker
Bring your own algorithms from local machine to SageMaker
SageMaker Pre built Algorithm
SageMaker Pipeline development
Schedule the SageMaker Training notebook
More than 5 hour course are provided which helps beginners to excel in SageMaker and will be well versed with build, train and deploy the models in SageMaker
Who this course is for:
- Data Engineers or data scientist
- Developers who want to start a career in or wants to learn about the exciting domain of Data Science and Machine Learning
- Business Analysts who want to apply Data Science to solve business problems
- Learn how to build train and deploy it in AWS cloud