- Published on July 11, 2019
- In Global Tech
Google Datalab Vs Amazon SageMaker: Which Cloud Platform Is Best For Your ML Project
- By Disha Misal
Deploying a machine learning service on a cloud platform is a huge advantage to all ML practitioners, as it provides a flexible platform for the design and development of various models. It provides serverless cloud engines giving the ML advantages of leveraging their models on a cloud platform since these are generally computationally heavy.
Google Datalab and Amazon SageMaker are very closely related to each other in many features, but also have many differences. Here is a detailed comparison between the two services/platforms:
1. Deployment
Google Datalab: The notebook server setup procedure is easy. It is launched using the Google cloud shell which is in the Google Cloud Console interface. Google Cloud SDK can also be used for notebook deployment.
Amazon SageMaker: Once logged into the SageMaker console, the deployment of the notebook is only a click away.
SageMaker wins.
2. Customised Algorithms
Google Datalab: It does not contain any pre-customised ML algorithms. B
📣 Want to advertise in AIM? Book here
Disha Misal
Found a way to Data Science and AI though her fascination for Technology. Likes to read, watch football and has an enourmous amount affection for Astrophysics.
Related Posts
AI’s Copyright Reckoning: Can India Balance Creators And Code?
From Hollywood studios to book publishers, copyright holders are pushing back against AI training.
AI is Redrawing VC Rules as Investors Hedge Bets Against Rival Startups
As AI reshapes markets, VC firms like Sequoia Capital are backing rival startups, raising fresh questions.
Inside IAIRO, India’s ISRO for AI
IAIRO is trying to create an ecosystem in India with funded labs, strong mentors, ambitious peers, and a culture of
For 25 Years, Wikipedia Trained AI. Now it Wants Payback
Wikipedia’s partnerships with Microsoft, Meta, Perplexity, Mistral, and Amazon have ushered it into the AI era.
Global AI Summits, Big Promises, No Rules: Will India’s Be Any Different?
The previous global AI summits have delivered failed promises of self-regulation by Big Tech and voluntary agreements lacking teeth.
How Agentic AI is Redesigning Job Roles for Engineers
EY research shows that 62% of employees in India are already using AI regularly at work.
AI is Forcing the End of Unit Testing. Here’s What It Means for Engineering Talent
The cost of such failures is enormous, forcing teams to rethink how early and how holistically they test.
India’s Big Tech Governance, Unchecked Tech Optimism Alarm Policy Advisors
Policy advisors and civil society groups accuse Big Tech of serving corporate interests with a hawkish AI push.
Download the easiest way to
stay informed
stay informed
