Requirements
- Basic understanding of Python Programming Language.
Description
Are you someone who wants to start their journey with AWS SageMaker – a cloud based service for building and deploying powerful Machine Learning products, then this course is for you.
Machine Learning is the future one of the top tech fields to be in right now! Machine Learning is widely adopted in Finance, banking, healthcare and technology. The field is exploding with opportunities and career prospects.
AWS is the one of the most widely used cloud computing platforms in the world and several companies depend on AWS for their cloud computing purposes. AWS SageMaker is a fully managed service offered by AWS that allows data scientist and AI practitioners to train, test, and deploy AI/ML models quickly and efficiently.
What will you learn ?
- Fundamental concepts of Data Science and Machine Learning.
- Build Machine Learning Models locally using sklearn.
- Model Evaluation metrics like accuracy, precision, MAE etc…
- HyperParameter Optimization for better performance of ML models.
- Basics of Cloud Computing.
- What and Why of Cloud Computing.
- What is AWS ?
- Different Services provided by AWS.
- AWS SageMaker – A complete solution to build and deploy powerful ML products on cloud.
- Build in deploy Machine Learning Projects on Cloud.
- Learn about powerful built in Machine Learning Algorithms in AWS SageMaker.
- No CODE Machine Learning using AWS SageMaker Canvas.
- AWS SageMaker marketplace – a place to buy state of the art pretrained ML models for direct use.
Who this course is for:
- Anyone who wants to get started with AWS SageMaker.
- Beginner Developers and Data Scientists who to learn about ML services on cloud and enhance their portfolio.
- Entrepreneurs and Consultants who want to take their business to next level using the power of AI and ML.
- Seasoned Data Scientists and ML Engineers who want to get started with AWS services for building powerful ML products.
Join us on Telegra
https://t.me/udemyfreedown
