June 09 2021

AWS SageMaker Complete Course| PyTorch & Tensorflow in NLP

AWS SageMaker Complete Course| PyTorch & Tensorflow in NLP
AWS SageMaker Complete Course| PyTorch & Tensorflow in NLP
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 2.24 GB
Genre: eLearning Video | Duration: 41 lectures (5 hour, 28 mins) | Language: English

Build deep learning model in Tensorflow/Keras & PyTorch.


How to bring docker container&Algorithm from local to Sagemaker
What you'll learn
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 example of NLP
How to schedule the SageMaker notebook for Retraining
How to Build ,deploy and schedule the Model
Requirements
Free or paid subscription to AWS is required. It may ask for Phone and/or Credit Card for verification
Python Basic knowledge
Description
This course is complete guide of AWS SageMaker wherein student will learn how to build, deploy SageMaker models by brining on-premises docker container and integrate it to SageMaker. Course will also do deep drive on how to bring your own algorithms in AWS SageMaker Environment. Course will also explain how to use pre-built optimized SageMaker Algorithm.
Course will also do deep drive how to create pipeline and workflow so model could be retrained and scheduled automatically.
This course will give you fair ideas of how to build Transformer framework in Keras for multi class classification use cases. Another way of solving multi class classification by using pre-trained model like Bert .
Both the Deep learning model later encapsulated in Docker in local machine and then later push back to AWS ECR repository.
This course offers:
What is SageMaker and why it is required
SageMaker Machine Learning lifecycle
SageMaker Architecture
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 bners to excel in SageMaker and will be well versed with build, train and deploy the models in SageMaker
Who this course is for:
Data Eeers 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




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