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Cloud Resources to run your Machine Learning and Deep Learning Models

amananandrai profile image amananandrai ・2 min read

Machine Learning requires a lot of resources for training its models. As normal people rarely possess devices with such high configurations it is the best option to run their models on Cloud. Deep Learning requires more amount of resources than traditional Machine learning models like SVM, Decision Trees and Random Forests etc. because it performs the task of Feature Extraction along with Training of models. The best way to run Deep Learning models is to host them on cloud and rent the resources. Some of the famous and good resources for running Machine Learning and Deep Learning models is listed below.

Google Colaboratory

This one of the most simple ways to run Machine Learning models. It allows you to create Jupyter notebooks. It also allows you to choose hardware between CPU, GPU, and TPU. The link to Google Colab is https://colab.research.google.com

Kaggle Kernels

Kaggle.com is the best community for Data scientists it provides Mini-Courses to learn DataScience and Kernels to run models. It is now owned by Google and Kaggle kernels are basically based on Google Colab. Kaggle kernels are now known as notebooks and the link is https://www.kaggle.com/notebooks


Paperspace is another very good alternative to host and run your ML models. It is very easy to deploy the models and it is also providing MLOps options. The link to paperspace is https://www.paperspace.com


This is a GPU rental platform where you can rent GPUs hourly based on your requirement and also the cost is flexible. The link to this resource rental platform is https://vast.ai

Oracle Cloud

This is the official cloud platform of Oracle. A person requires some experience in deploying their application here. It can be used for many purposes other than Deep Learning and Machine Learning. The link to the cloud by oracle is https://www.oracle.com/cloud

Amazon Web Services(AWS)

AWS as it is popularly known is the most popular Cloud Hosting platform. It is also multipurpose and can be used for other tasks. The link to AWS is https://aws.amazon.com

Microsoft Azure

The Microsoft alternative of AWS. In these platforms one requires some training before running their application or train their models. The link to Microsoft Azure is https://azure.microsoft.com

Google Cloud Platform(GCP)

It is another option from Google for hosting on Cloud not limited to ML and DL. It can be termed as the alternative to AWS. The link to Cloud Platform by Google is https://cloud.google.com

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