Found 46 repositories(showing 30)
@DeepLearning.AI Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It has helped me to develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker.
This repository contains my code solution to DeepLearning.AIs Practical Data Science On AWS Cloud Specialization.
ShrutikaKharat
Development environments might not have the exact requirements as production environments. Moving data science and machine learning projects from idea to production requires state-of-the-art skills. You need to architect and implement your projects for scale and operational efficiency. Data science is an interdisciplinary field that combines domain knowledge with mathematics, statistics, data visualization, and programming skills. The Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It helps you develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker. This Specialization is designed for data-focused developers, scientists, and analysts familiar with the Python and SQL programming languages who want to learn how to build, train, and deploy scalable, end-to-end ML pipelines - both automated and human-in-the-loop - in the AWS cloud. Each of the 10 weeks features a comprehensive lab developed specifically for this Specialization that provides hands-on experience with state-of-the-art algorithms for natural language processing (NLP) and natural language understanding (NLU), including BERT and FastText using Amazon SageMaker. Applied Learning Project By the end of this Specialization, you will be ready to: • Ingest, register, and explore datasets • Detect statistical bias in a dataset • Automatically train and select models with AutoML • Create machine learning features from raw data • Save and manage features in a feature store • Train and evaluate models using built-in algorithms and custom BERT models • Debug, profile, and compare models to improve performance • Build and run a complete ML pipeline end-to-end • Optimize model performance using hyperparameter tuning • Deploy and monitor models • Perform data labeling at scale • Build a human-in-the-loop pipeline to improve model performance • Reduce cost and improve performance of data products
@DeepLearning.AI Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It has helped me to develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker.
FabianCoyDuarte
Coursera Course with a lot of practices resources and examples to deploy
Practical Data Science on the AWS Cloud Specialization
sergiobg76
Coursera files from the completion of course "Practical Data Science On AWS Cloud"
saratbhargava
Codes from the Practical Data Science course from Deeplearning.ai website.
edoardo132
Specialization course offered by Deeplearning.ai and AWS
aleynadikall
Coursera Kursu : Amazon SageMaker kullanarak veri bilimi projelerini buluta taşıma ve ölçeklendirme
No description available
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adigew
Practical Data Science on the AWS Cloud
lvallejomendez
Practical Data Science on the AWS Cloud Specialization
keerthikhot
No description available
dileepkanumuri
In this Repo, I'll upload all my leanings & my own hand on experience projects based on the specialization taught by Sireesha Muppala and other AWS instructors
priyanka-asnani
Specialization offered by AWS
martinAmouzou
No description available
CreaperLost
All code, and notebooks wrote for the assignments of Practical Data Science on the AWS Cloud provide by Deep Learning AI on Coursera.
10 learning projects using AWS SageMaker.
tanvir1985
No description available
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hafizhassaan
No description available
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No description available
This repo contains my lab files for Data Science AWS specialization offered by Coursera.
Devender-Singh-P
Practical Data Science on the AWS Cloud Specialization on Coursera
No description available
No description available
Coursera courses by Antje Barth, Sireesha Muppala, Shelbee Eigenbrode, and Chris Fregly