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How BigBasket improved AI-enabled checkout at their physical stores using Amazon SageMaker

AWS Machine Learning

SageMaker provides end-to-end ML development, deployment, and monitoring capabilities such as a SageMaker Studio notebook environment for writing code, data acquisition, data tagging, model training, model tuning, deployment, monitoring, and much more.

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Are softer skills for analysts being neglected?

Peter Lavers

In my new line of work, I get to speak at industry conferences, read data/analytics/research publications and scan the plethora of blogs or social media comments on this topic. Ever since Google made “ data scientist ” the sexy job title for the decade, both suppliers and users have obsessed with technology and technical skills.

CRM 100
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Scary but True, Pt. 2: Artificial Intelligence Is Coming for Your Job

Mindtouch

But AI like Salesforce’s Einstein is beginning to help shape the way that businesses use Big Data. 3: Google and the IoT Are Tag-Teaming to Kill Your Website. 2: Artificial Intelligence Is Coming for Your Job appeared first on MindTouch Blog. in our Iron Man suits). Scary but True, Pt. 1: How Marketing Gets Out-Marketed.

CRM 48
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Debunking Natural Language Processing: Detecting Events

Clarabridge

In the previous blog posts , we discussed some of the ways in which Clarabridge uses Named Entity Recognition to find meaning within customer feedback. In addition to detecting the named entities described in previous sections, Clarabridge automatically tags events of all kinds. Specific events also help keep certain businesses afloat.

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Intelligent document processing with AWS AI services: Part 2

AWS Machine Learning

In part 1, we described the data capture and document classification stages, where we categorized and tagged documents such as bank statements, invoices, and receipt documents. For simplicity of this blog post, we use the entity lists method, which you can only use for plain text documents.

Banking 75
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Large-scale feature engineering with sensitive data protection using AWS Glue interactive sessions and Amazon SageMaker Studio

AWS Machine Learning

For DataEngineerPwd and DataScientistPwd , enter your own password for the data engineer and data scientist users. For S3BucketNameForInput , enter blog-studio-pii-dataset-. For S3BucketNameForOutput , enter blog-studio-output-. For Tags , add the key userprofilename and the value data-engineer. Choose Next.

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Accelerate time to insight with Amazon SageMaker Data Wrangler and the power of Apache Hive

AWS Machine Learning

Starting today, you can connect to Amazon EMR Hive as a big data query engine to bring in large datasets for ML. Aggregating and preparing large amounts of data is a critical part of ML workflow. Data scientists and data engineers use Apache Spark, Apache Hive, and Presto running on Amazon EMR for large-scale data processing.