Jupyter notebooks for labs and testing on Amazon SageMaker.
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Updated
Apr 7, 2021 - Jupyter Notebook
Amazon Web Services (AWS) is a subsidiary of Amazon.com that provides on-demand cloud computing platforms to individuals, companies, and governments, on a subscription basis. Compute, storage, database, networking, security, management & developer tools, AI & machine learning, analytics, etc. are some of the primary aspects of AWS.
Jupyter notebooks for labs and testing on Amazon SageMaker.
Notebooks from MLOps course in AWS. AWS python sdk.
Data Science python notebooks (ktrain, AWS).
Use Jupyter notebooks in your notebook instance to prepare and process data, write code to train models, deploy models to SageMaker hosting, and test or validate your models.
Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Recommendation System using Factorization Machines - AWS SageMaker NoteBook Instance
example notebooks for common DS/ML libraries in python
📓 The not so "Getting Started" manual most never read.
Jupyter notebooks to help team members utilize AWS SageMaker tools
Practice examples using Google Colab Notebooks: working with big data
Implement pipeline between services, notebook, aws for automate recommendation engine
Various Template Notebooks for Deploying ML models with Amazon Sagemaker
Notebooks supporting the activities for generative AI 102 Startup loft.
Bash Script that helps you deploy Jupyter Notebook on AWS EC2 Instance
Helps copy AWS QuickSight Dataset, themes and Dashboard to different account
This repository contains all the assignment notebooks of the course, AWS Computer Vision: Getting Started with GluonCV.
Released March 2006