AI With AWS Online Training | AWS AI Course

What is Amazon
SageMaker? An
Overview in
AI with AWS
+91-9989971070  
Amazon SageMaker is a fully managed machine learning
(ML) service provided by Amazon Web Services (AWS),
designed to empower developers and data scientists to
build, train, and deploy machine learning models at scale.
As a cornerstone of AI with AWS, SageMaker streamlines
the entire ML lifecycle, making it accessible even to those
with minimal expertise in machine learning.
www.visualpath.in
Key Features of Amazon SageMaker
Simplified ML Development
SageMaker eliminates the need for extensive
infrastructure management. It offers pre-configured
Jupyter notebooks, enabling data exploration and
preprocessing with ease. Integrated tools, such as built-
in algorithms and support for popular ML frameworks
like TensorFlow and PyTorch, ensure seamless model
development.
www.visualpath.in
Automated Model Training
SageMaker's training capabilities are robust and
efficient. Users can choose to train models on custom
datasets or leverage AWS’s managed datasets. The
service supports automatic model tuning
(hyperparameter optimization), allowing users to
achieve optimal performance without extensive manual
effort.
www.visualpath.in
Easy Deployment and Management
Deploying machine learning models is often complex,
but SageMaker simplifies the process with one-click
deployment. Models can be hosted on scalable
endpoints, ensuring they can handle real-time
predictions with low latency. Additionally, SageMaker
offers monitoring tools to track model performance
post-deployment.
www.visualpath.in
End-to-End Workflow Support
SageMaker supports every stage of the ML workflow,
from data preparation to deployment. It includes tools
like SageMaker Data Wrangler for preprocessing,
SageMaker Studio for collaboration, and SageMaker
Clarify for bias detection and explainability in models.
www.visualpath.in
Scalability and Cost Efficiency
As a cloud-native service, SageMaker allows users to
scale their resources based on demand. Its pay-as-you-
go pricing ensures cost efficiency, making it ideal for
both startups and enterprises.
www.visualpath.in
Applications of Amazon SageMaker
SageMaker is used across industries for applications
such as:
Predictive analytics in finance
Personalized recommendations in e-commerce
Fraud detection in banking
Advanced forecasting in supply chain management
www.visualpath.in
Why Choose SageMaker for AI on AWS?
SageMaker integrates seamlessly with other AWS
services like S3, Lambda, and Athena, creating a
powerful ecosystem for building AI solutions. By
removing the complexities of ML development and
deployment, SageMaker accelerates innovation,
enabling businesses to focus on deriving value from AI.
www.visualpath.in
In summary,
Amazon SageMaker democratizes AI by providing a
user-friendly platform for ML practitioners of all skill
levels. Its comprehensive features make it a critical tool
for anyone exploring 
AI with AWS
.
www.visualpath.in
CONTACT
CONTACT
For More Information About
AI With AWS Online Training
Address:- 
Flat no: 205, 2nd Floor,
                                   Nilagiri Block, Aditya Enclave,
                            Ameerpet, Hyderabad-16
 Ph No : 
+91-9989971070
        
Visit : 
www.visualpath.in
      
E-Mail  : 
online@visualpath.in
                 
THANK YOU
                         Visit: 
www.visualpath.in
Slide Note
Embed
Share

Visualpath offers the Best AWS AI Course conducted by real-time experts. Learn the fundamentals of Artificial Intelligence (AI) on AWS. Prepare for AWS AI certification. Get hands-on AWS AI training in Hyderabad and is provided individually, globall

  • Ai
  • AWS
  • AWS Sagemaker
  • AWS AI Services
  • Deep Learning

Uploaded on Nov 22, 2024 | 2 Views


Download Presentation

Please find below an Image/Link to download the presentation.

The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.

You are allowed to download the files provided on this website for personal or commercial use, subject to the condition that they are used lawfully. All files are the property of their respective owners.

The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.

E N D

Presentation Transcript


  1. What is Amazon SageMaker? An Overview in AI with AWS +91-9989971070 www.visualpath.in

  2. Amazon SageMaker is a fully managed machine learning (ML) service provided by Amazon Web Services (AWS), designed to empower developers and data scientists to build, train, and deploy machine learning models at scale. As a cornerstone of AI with AWS, SageMaker streamlines the entire ML lifecycle, making it accessible even to those with minimal expertise in machine learning. www.visualpath.in

  3. Key Features of Amazon SageMaker Simplified ML Development SageMaker eliminates the need for extensive infrastructure management. It offers pre-configured Jupyter notebooks, enabling data exploration and preprocessing with ease. Integrated tools, such as built- in algorithms and support for popular ML frameworks like TensorFlow and PyTorch, ensure seamless model development. www.visualpath.in

  4. Automated Model Training SageMaker's training capabilities are robust and efficient. Users can choose to train models on custom datasets or leverage AWS s managed datasets. The service supports automatic (hyperparameter optimization), allowing users to achieve optimal performance without extensive manual effort. www.visualpath.in model tuning

  5. Easy Deployment and Management Deploying machine learning models is often complex, but SageMaker simplifies the process with one-click deployment. Models can be hosted on scalable endpoints, ensuring they can handle real-time predictions with low latency. Additionally, SageMaker offers monitoring tools to track model performance post-deployment. www.visualpath.in

  6. End-to-End Workflow Support SageMaker supports every stage of the ML workflow, from data preparation to deployment. It includes tools like SageMaker Data Wrangler for preprocessing, SageMaker Studio for collaboration, and SageMaker Clarify for bias detection and explainability in models. www.visualpath.in

  7. Scalability and Cost Efficiency As a cloud-native service, SageMaker allows users to scale their resources based on demand. Its pay-as-you- go pricing ensures cost efficiency, making it ideal for both startups and enterprises. www.visualpath.in

  8. Applications of Amazon SageMaker SageMaker is used across industries for applications such as: Predictive analytics in finance Personalized recommendations in e-commerce Fraud detection in banking Advanced forecasting in supply chain management www.visualpath.in

  9. Why Choose SageMaker for AI on AWS? SageMaker integrates seamlessly with other AWS services like S3, Lambda, and Athena, creating a powerful ecosystem for building AI solutions. By removing the complexities of ML development and deployment, SageMaker enabling businesses to focus on deriving value from AI. www.visualpath.in accelerates innovation,

  10. In summary, Amazon SageMaker democratizes AI by providing a user-friendly platform for ML practitioners of all skill levels. Its comprehensive features make it a critical tool for anyone exploring AI with AWS. www.visualpath.in

  11. CONTACT For More Information About AI With AWS Online Training Address:- Flat no: 205, 2nd Floor, Nilagiri Block, Aditya Enclave, Ameerpet, Hyderabad-16 Ph No : +91-9989971070 Visit : www.visualpath.in E-Mail : online@visualpath.in

  12. THANK YOU Visit: www.visualpath.in

Related


More Related Content

giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#