Name: Amazon Tensor Flow
Rating: 8 (5 reviews)
Author: Amazon AWS

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Amazon Tensor Flow

Machine learning tools are algorithmic applications of artificial intelligence that give systems the ability to learn and improve without ample human input; similar concepts are data mining and predictive modeling. They allow software to become more accurate in predicting outcomes without being explicitly programmed. The idea is that a model or algorithm is used to get data from the world, and that data is fed back into the model so that it improves over time. It’s called machine learning because the model “learns” as it is fed more and more data.

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Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce platform.

Founded by Jeff Bezos, the Amazon.com website started in 1995 as a place to buy books because of the unique customer experience the Web could offer book lovers. Bezos believed that only the Internet could offer customers the convenience of browsing a selection of millions of book titles in a single sitting. During the first 30 days of business, Amazon fulfilled orders for customers in 50 states and 45 countries - all shipped from his Seattle-area garage.

Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world's brightest technology minds come to Amazon.com to research and develop technology that improves the lives of shoppers and sellers around the world.

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Amazon Tensor Flow 2019-01-14 18:31:57

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We use Amazon Tensor Flow mainly for classification, regression, and clustering when using large databases and for overseas clients. The cloud capabilities allow us to smoothly provide a full service for our clients overseas

Amazon Elastic Compute Cloud (EC2) allows resizable compute capacity in the cloud, providing the necessary elasticity to provide services for both, small and medium-sized businesses.
Tensor Flow allows us to train our models much faster than in our on-premise equipment.
Most of the pre-trained models are easy to adapt to our clients' needs.

SageMaker isn't available in all regions. This is complicated for some clients overseas.
For larger instances, when using a GPU, it takes a while to talk to a customer service representative to ask for a limit increase. Given this, it's recommendable to ask in advance for a limit increase in more expensive and larger cases; otherwise, SageMaker will set the limit to zero by default.
Since the data has to be stored in S3 and copied to training, it doesn't allow to test and debug locally. Therefore, we have to wait a lot to check everything after every trail.

Positive: It has allowed us to work with our overseas teams without any large hardware investing.
Positive: Pre-trained models significantly reduce the time to develop solutions for our clients.
Negative: Since it's a relatively new tool, you have to be careful about not paying for large errors while learning to use the tool.

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Amazon Tensor Flow

Overview

What is Amazon Tensor Flow?