AWS Machine Learning

JULY 19, 2022

To test the model output, we use a Jupyter notebook to run Python code to detect custom labels in a supplied image by calling Amazon Rekognition APIs. The solution workflow is as follows: Store satellite imagery data in Amazon S3 as the input source. Store satellite imagery data in Amazon S3 as an input source.

APIs 70

APIs Metrics Enterprise Government 70

AWS Machine Learning

DECEMBER 1, 2022

A well-implemented model governance framework should minimize the number of interfaces required to view, track, and manage lifecycle tasks to make it easier to monitor the ML lifecycle at scale. With the SageMaker Python SDK, you can seamlessly update the Model card with evaluation metrics. Define and capture custom information.

Government 78

Government Metrics APIs Engineering 78

AWS Machine Learning

MAY 3, 2023

This post is focused around the third point in this list and shows how to achieve dynamic scaling of SageMaker Processing jobs to achieve a more managed, performant, and cost-effective data processing framework for large data volumes. This type of alarm (metric) uses CloudWatch alarm thresholds.

Engineering 70

Engineering Metrics APIs Big data 70

AWS Machine Learning

JULY 24, 2023

Patsnap provides a global one-stop platform for patent search, analysis, and management. They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. implement the model and the inference API. Specifically, Dockerfile and build.sh gpt2 and predictor.py client('sts').get_caller_identity()['Account']

APIs 66

APIs Engineering Construction Benchmark 66

Spearline

JANUARY 23, 2018

An API (Application Programming Interface) will enhance your utilisation of our platform. Our RESTful API provides your developers with the ability to create campaigns, add numbers, time groups, export data for every test run, every day, every hour, every minute if that’s what you need to put your arms around your business.

Call flow 40

Call flow Benchmark APIs Big data 40

AWS Machine Learning

JULY 21, 2022

As a result, this experimentation phase can produce multiple models, each created from their own inputs (datasets, training scripts, and hyperparameters) and producing their own outputs (model artifacts and evaluation metrics). SageMaker Experiments allows data scientists organize, track, compare, and evaluate their training iterations.

Metrics 77

Metrics Scripts Enterprise Telecommunications 77

AWS Machine Learning

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs.

Best practices 122

Best practices Government Engineering Accountability 122

aircall

APRIL 16, 2021

Establish performance metrics (response time, retention, engagement, etc.). SaaS works well for a variety of general use cases, including: Data backup. Big data analytics. Flexibility – SaaS uses an open API (application programming interface) technology. 8) Failing to track metrics. troubleshooting.

SaaS 62

SaaS Sales Coaching APIs 62

AWS Machine Learning

JUNE 15, 2022

Edge is a term that refers to a location, far from the cloud or a big data center, where you have a computer device (edge device) capable of running (edge) applications. When you scale your system, it’s important to have a robust solution that can manage the number of devices that you need to support. Edge computing.

Transportation 76

Transportation APIs Big data Wireless 76

AWS Machine Learning

SEPTEMBER 9, 2022

Its electronic health records, revenue cycle management, and patient engagement tools allow anytime, anywhere access, driving better financial outcomes for its customers and enabling its provider customers to deliver better quality care. Amazon CloudWatch for persistent log management.

Engineering 75

Engineering Healthcare APIs Scripts 75

Xaqt

FEBRUARY 6, 2020

Back in the winter of 2005, Jason Kolb (my cofounder and CTO of Latigent) and I penned an article for Business Management magazine titled BI with an IQ. Back then, Artificial Intelligence, APIs, Robotic Process Automation (RPA), and even "Big Data" weren't things yet. technologies were first emerging. Don't believe me?

Contact Center 52

Contact Center Enterprise Call Center APIs 52

AWS Machine Learning

JULY 25, 2022

For production, we wanted to invoke the model as a simple API call. We found that we didn’t need to separate data preparation, model training, and prediction, and it was convenient to package the whole pipeline as a single script and use SageMaker processing. With other standard metrics, the improvement ranged from 50–130%.

Scripts 70

Scripts Engineering Analytics APIs 70

AWS Machine Learning

NOVEMBER 14, 2023

In the era of big data and AI, companies are continually seeking ways to use these technologies to gain a competitive edge. At the core of these cutting-edge solutions lies a foundation model (FM), a highly advanced machine learning model that is pre-trained on vast amounts of data.

Management 89

Management APIs Best practices Calibration 89

Xaqt

JUNE 22, 2020

Despite significant advancements in big data and open source tools, niche Contact Center Business Intelligence providers are still wed to their own proprietary tools leaving them saddled with technical debt and an inability to innovate from within. Out with the old guard, in with the new.

Call Center 52

Call Center Contact Center Analytics Engineering 52

AWS Machine Learning

JUNE 24, 2022

The deployment of the ML pipelines is driven only via CI/CD pipelines, and the access to the AWS Management Console is restricted. Internet connection is not allowed because the ML pipeline has access to production data in the data lake (read-only). Data lake and MLOps integration.

Enterprise 89

Enterprise Engineering Accountability APIs 89

aircall

MARCH 19, 2021

With all the available customer data companies have at their disposal to enhance the performance of customer service, sales, and marketing efforts, a remarkable 73% of companies still do not use it effectively. And out of those who do practise data collection, only 12% analyze it. Best Practices of Customer Data Management.

Sales 62

Sales CRM Marketing Best practices 62

AWS Machine Learning

MAY 8, 2023

With Amazon SageMaker , you can manage the whole end-to-end machine learning (ML) lifecycle. It offers many native capabilities to help manage ML workflows aspects, such as experiment tracking, and model governance via the model registry. Now let’s dive deeper into the details.

APIs 70

APIs Government Accountability Scripts 70

AWS Machine Learning

FEBRUARY 1, 2024

Observability Besides the resource metrics you typically collect, like CPU and RAM utilization, you need to closely monitor GPU utilization if you host a model on Amazon SageMaker or Amazon Elastic Compute Cloud (Amazon EC2). He entered the big data space in 2013 and continues to explore that area.

Best practices 111

Best practices Engineering SaaS APIs 111

Enghouse Interactive

JULY 10, 2018

Contact Babel 2017 DMG says, “It can be stated with some confidence that first-contact resolution is seen as the key to a successful contact center: 76% of the report’s respondents place first-contact resolution as being one of the top 3 metrics that are most influential on customer satisfaction, with 31% stating it as being no.1.”.

Self service 40

Self service CRM Contact Center Analytics 40

AWS Machine Learning

DECEMBER 18, 2023

Industries such as Finance, Retail, Supply Chain Management, and Logistics face the risk of missed opportunities, increased costs, inefficient resource allocation, and the inability to meet customer expectations. In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution.

Finance 104

Finance APIs Analytics Scripts 104

AWS Machine Learning

JANUARY 4, 2024

NLP SQL enables business users to analyze data and get answers by typing or speaking questions in natural language, such as the following: “Show total sales for each product last month” “Which products generated more revenue?” In entered the Big Data space in 2013 and continues to explore that area. Arghya Banerjee is a Sr.

Best practices 119

Best practices Enterprise Engineering APIs 119

AWS Machine Learning

AUGUST 29, 2023

The presented MLOps workflow provides a reusable template for managing the ML lifecycle through automation, monitoring, auditability, and scalability, thereby reducing the complexities and costs of maintaining batch inference workloads in production.

Scripts 73

Scripts APIs Enterprise Accountability 73

SmartKarrot

JUNE 23, 2020

For instance, can a Customer Success Manager (CSM) forecast retention and revenue rates based on users’ behaviour? Enter the SaaS dragon – data. Without analytics, collation of behavioural data is a waste. Without analytics, CS teams can only rely on insufficient demographic data, or what’s called ‘vanity metrics.

Analytics 10

Analytics SaaS Upselling Entertainment 10