Aws AI Training In Hyderabad | Aws AI Course
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
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. Download presentation by click this link. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.
E N D
Presentation Transcript
What is ML on AWS? Machine Learning (ML) on AWS (Amazon Web Services) refers to the comprehensive suite of tools, services, and infrastructure provided by AWS to enable organizations and developers to build, train, and deploy ML models efficiently. AWS offers a scalable, secure, and cost- effective environment that supports both beginners and experts in their ML journey, whether for small experiments or large-scale deployments. AWS AI Certification Key Components of ML on AWS 1. Amazon SageMaker Amazon SageMaker is the flagship ML service on AWS. It provides an integrated environment to prepare data, build, train, and deploy ML models. It eliminates much of the heavy lifting traditionally involved in ML workflows by offering pre-built algorithms, model tuning, and fully managed infrastructure. AWS AI Course 2. Pre-trained AI Services AWS provides a range of AI services powered by pre-trained ML models, enabling businesses to quickly implement ML features without extensive knowledge of data science. Popular services include: AWS AI Online Training Amazon Rekognition for image and video analysis. Amazon Comprehend for natural language processing (NLP). Amazon Polly for text-to-speech conversion. Amazon Textract for extracting text and data from documents. 3. Compute and Storage
AWS offers scalable compute options like EC2 instances optimized for ML tasks (e.g., GPU- powered instances) and storage solutions such as Amazon S3 and EFS for managing large datasets critical to ML projects. 4. Framework Support AWS supports popular ML frameworks like TensorFlow, PyTorch, and Scikit-learn, ensuring flexibility for developers. AWS Deep Learning AMIs (Amazon Machine Images) come pre- installed with these frameworks, making it easier to start ML projects. 5. MLOps and Automation AWS enables MLOps (Machine Learning Operations) to streamline the deployment and monitoring of ML models in production. Features like SageMaker Pipelines and Model Monitor help automate workflows and ensure model reliability. Benefits of ML on AWS Scalability: Elastic infrastructure accommodates varying workloads. Cost Efficiency: Pay-as-you-go pricing reduces expenses for experimentation and scaling. Security: AWS offers enterprise-grade security, compliance certifications, and tools like IAM to control access. Ease of Use: A wealth of documentation, tutorials, and tools support seamless adoption. Conclusion ML on AWS empowers organizations to integrate machine learning into their operations efficiently. Whether through pre-built AI services or custom model development with Amazon SageMaker, AWS provides the flexibility and resources to innovate across industries like healthcare, finance, retail, and more. Visualpath is the Leading and Best Software Online Training Institute in Hyderabad. Avail complete AI With AWS institute in Hyderabad AWS AI Course Worldwide. You will get the best course at an affordable cost. Attend Free Demo Call on - +91-9989971070. Visit Blog: https://visualpathblogs.com/ WhatsApp: https://www.whatsapp.com/catalog/919989971070
