AWS Machine Learning

SEPTEMBER 9, 2022

Amp wanted a scalable data and analytics platform to enable easy access to data and perform machine leaning (ML) experiments for live audio transcription, content moderation, feature engineering, and a personal show recommendation service, and to inspect or measure business KPIs and metrics. Solution overview.

Analytics 69

Analytics Engineering APIs Metrics 69

AWS Machine Learning

FEBRUARY 2, 2023

The data distribution for punt and kickoff are different. Data preprocessing and feature engineering First, the tracking data was filtered for just the data related to punts and kickoff returns. As a baseline, we used the model that won our NFL Big Data Bowl competition on Kaggle.

Calibration 74

Calibration Engineering Big data Automotive 74

AWS Machine Learning

DECEMBER 21, 2022

As feature data grows in size and complexity, data scientists need to be able to efficiently query these feature stores to extract datasets for experimentation, model training, and batch scoring. SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation.

Scripts 73

Scripts Engineering APIs Big data 73

AWS Machine Learning

FEBRUARY 15, 2024

With the use of cloud computing, big data and machine learning (ML) tools like Amazon Athena or Amazon SageMaker have become available and useable by anyone without much effort in creation and maintenance. The predicted value indicates the expected value for our target metric based on the training data.

Metrics 91

Metrics Analytics APIs Big data 91

SharpenCX

OCTOBER 7, 2022

In an AI exercise, if the vendor keeps asking for more and more data, that is a red flag. It basically means that the lab-version of their model, with your data, is not seeing results. Start asking for model validation graphs on contact center performance metrics. Be wary of “statistics-speak”. Keep perspective.

Contact Center 67

Contact Center Contact center software Big data Engineering 67

CustomerSuccessBox

MAY 30, 2022

To identify a watermelon customer, the metric that would help you the most is instead the Customer Intent Score. The Customer Intent Score is a metric that measures a visitor’s willingness to accomplish a conversion goal, for example- a request for further information. Just imagine the enormity of untracked data.

Upselling 52

Upselling Calibration Engineering Big data 52

AWS Machine Learning

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Best practices 122

Best practices Government Engineering Accountability 122

AWS Machine Learning

JULY 24, 2023

This blog post was co-authored, and includes an introduction, by Zilong Bai, senior natural language processing engineer at Patsnap. They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. Zilong Bai is a senior natural language processing engineer at Patsnap.

APIs 66

APIs Engineering Construction Benchmark 66

BlueOcean

DECEMBER 18, 2018

In their answers to the following questions, they should be addressing chatbots, self-service, machine learning, big data, and more. AI can be a powerful tool, but it is just one cog in the customer care engine. 5 What KPIs/metrics do you measure in tracking the effectiveness of your escalations from AI to live agent?

Contact Center 78

Contact Center Chatbots outsourcing Metrics 78

Natalie Petouhof

OCTOBER 12, 2016

DPM vendors help both the business and engineering teams to not only define conversion and revenue goals but also make sure they are reached. Big data monitoring and data visualization  . When DPM is optimized, companies can deliver an engaging digital experience, maximize revenue and improve brand loyalty.

Management 55

Management Big data Analytics Engineering 55

Real Blue Sky

NOVEMBER 16, 2022

When paired with chatbots or natural language engines, AI can identify a repeat caller, ask if the prior issue was resolved and, if not, serve up a specialized agent with pertinent details from the prior encounter (including transcriptions), to set the stage for full resolution. Use predictive data for marketing.

Customer Experience 52

Customer Experience Chatbots CRM Analytics 52

Real Blue Sky

NOVEMBER 16, 2022

When paired with chatbots or natural language engines, AI can identify a repeat caller, ask if the prior issue was resolved and, if not, serve up a specialized agent with pertinent details from the prior encounter (including transcriptions), to set the stage for full resolution. Use predictive data for marketing.

Customer Experience 52

Customer Experience Chatbots CRM Analytics 52

Real Blue Sky

NOVEMBER 16, 2022

When paired with chatbots or natural language engines, AI can identify a repeat caller, ask if the prior issue was resolved and, if not, serve up a specialized agent with pertinent details from the prior encounter (including transcriptions), to set the stage for full resolution. Use predictive data for marketing.

Customer Experience 52

Customer Experience Chatbots CRM Analytics 52

AWS Machine Learning

APRIL 24, 2023

We invoke a Lambda function to validate that the training data path exists, and then trigger an Amazon Comprehend training job. If the training job is complete, we get the model metric and store it in DynamoDB for further evaluation. Before joining AWS, she was a software engineer. Shanna Chang is a Solutions Architect at AWS.

APIs 62

APIs Customer Experience Feedback Chatbots 62

Xaqt

FEBRUARY 6, 2020

Back then, Artificial Intelligence, APIs, Robotic Process Automation (RPA), and even "Big Data" weren't things yet. There are also drill-down reports that promise to let your managers slice and dice their data anyway they choose. Rewind it Back Let's take a look back to 2005 when "Web 2.0" technologies were first emerging.

Contact Center 52

Contact Center Enterprise Call Center APIs 52

Talkdesk

FEBRUARY 23, 2017

In this post, we’ll cover a couple of ways to use big data to assist in predictive customer service attempts. When it comes to customers, there’s all sort of data to review, but as far as customer service is concerned, it’s vital that companies know the issues customers are having at various stages of their product usage.

Customer Service 40

Customer Service Best practices Big data Metrics 40

AWS Machine Learning

FEBRUARY 2, 2024

You can run the notebook pattern1-rag/notebooks/distance-analysis.ipynb to see the trends in the distance metrics over time. Randy has held a variety of positions in the technology space, ranging from software engineering to product management. In entered the Big Data space in 2013 and continues to explore that area.

Big data 91

Big data Technology Management Engineering 91

AWS Machine Learning

NOVEMBER 9, 2023

Machine Learning Engineer with AWS Professional Services. Prior to this role, she led multiple initiatives as a data scientist and ML engineer with top global firms in the financial and retail space. She holds a master’s degree in Computer Science specialized in Data Science from the University of Colorado, Boulder.

Scripts 99

Scripts Accountability Engineering Best practices 99

AWS Machine Learning

OCTOBER 1, 2022

The first component of the three input dimensions consists of a feature set that describes the current game action in real time for both teams in performance metrics. His skills and areas of expertise include application development, data science, machine learning, and big data.

Telecommunications 78

Telecommunications Consulting Consulting Big data 78

Clarabridge

FEBRUARY 14, 2017

Because of this root cause analysis, the engineering team redesigned the headrest fastening system. It’s not always easy to find the root cause when you first notice a change in your metrics. It shows you what is really driving your metrics, and gives you a chance to fix what’s wrong. They were easier to remove and replace.

Engineering 53

Engineering Metrics Analytics Feedback 53

AWS Machine Learning

MARCH 15, 2024

Randy has held a variety of positions in the technology space, ranging from software engineering to product management. He entered the big data space in 2013 and continues to explore that area. Prior to joining AWS, Arnab was a technology leader and previously held architect and engineering leadership roles.

Healthcare 106

Healthcare Big data Engineering Accountability 106

Clarabridge

FEBRUARY 14, 2017

Because of this root cause analysis, the engineering team redesigned the headrest fastening system. It’s not always easy to find the root cause when you first notice a change in your metrics. It shows you what is really driving your metrics, and gives you a chance to fix what’s wrong. They were easier to remove and replace.

Engineering 40

Engineering Metrics Analytics Feedback 40

Clarabridge

FEBRUARY 14, 2017

Because of this root cause analysis, the engineering team redesigned the headrest fastening system. It’s not always easy to find the root cause when you first notice a change in your metrics. It shows you what is really driving your metrics, and gives you a chance to fix what’s wrong. They were easier to remove and replace.

Engineering 40

Engineering Metrics Analytics Feedback 40

AWS Machine Learning

JANUARY 4, 2024

Specifically, we discuss the following: Why do we need Text2SQL Key components for Text to SQL Prompt engineering considerations for natural language or Text to SQL Optimizations and best practices Architecture patterns Why do we need Text2SQL? Effective prompt engineering is key to developing natural language to SQL systems.

Best practices 119

Best practices Enterprise Engineering APIs 119

Callminer

NOVEMBER 6, 2019

Big data is getting bigger with each passing year, but making sense of trends hidden deep in the heap of 1s and 0s is more confounding than ever. As metrics pile up, you may find yourself wondering which data points matter and in what ways they relate to your business’s interests.

Big data 140

Big data Analytics Metrics Sales 140

AWS Machine Learning

FEBRUARY 1, 2024

There are unique considerations when engineering generative AI workloads through a resilience lens. Make sure to validate prompt input data and prompt input size for allocated character limits that are defined by your model. If you’re performing prompt engineering, you should persist your prompts to a reliable data store.

Best practices 112

Best practices Engineering SaaS APIs 112

Comm100

SEPTEMBER 22, 2016

How to Build Your Customer-Driven Growth Engine by Jeanne Bliss. How to Revolutionize Customer Employee Engagement with Big Data and Gamification by Rajat Paharia. focuses on how to use big data and gamification to engage your customers more than ever before. Chief Customer Officer 2.0: Loyalty 3.0:

Customer Service 70

Customer Service Gamification Consulting Consulting 70

AWS Machine Learning

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. JuMa is now available to all data scientists, ML engineers, and data analysts at BMW Group.

Engineering 72

Engineering Analytics Government Self service 72

SmartKarrot

JANUARY 28, 2022

We see an expansion in the roles coming up in this field, including onboarding managers, CS engineers, support, renewal managers … the list goes on. AI and ML can help you generate metadata data, engagement data, and product adoption data to learn the renewal history that helps decode what drives the renewals and upsells.

B2B 10

B2B SaaS Upselling Metrics 10

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

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

FEBRUARY 29, 2024

This enables data scientists to quickly build and iterate on ML models, and empowers ML engineers to run through continuous integration and continuous delivery (CI/CD) ML pipelines faster, decreasing time to production for models. Solution overview The proposed framework code starts by reading the configuration files. The model_unit.py

Scripts 92

Scripts Engineering Metrics Best practices 92

AWS Machine Learning

DECEMBER 18, 2023

When the model is ready, select the model and click on the latest version Review the model metrics and column impact and if you are satisfied with the model performance, click Predict. Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem.

Finance 104

Finance APIs Analytics Scripts 104

Vistio

OCTOBER 5, 2021

And you can look at various specific areas such as data analytics, big data, being able to study patterns within data, using artificial intelligence or using machine learning to actually gather up every customer interaction, and remember the original problem and the solution.

Chatbots 52

Chatbots Contact Center Banking Technology 52

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). We also illustrate how you can track your pipeline workflow and generate metrics and comparison charts.

Metrics 77

Metrics Scripts Enterprise Telecommunications 77

AWS Machine Learning

DECEMBER 1, 2022

With the SageMaker Python SDK, you can seamlessly update the Model card with evaluation metrics. Model cards provide model risk managers, data scientists, and ML engineers the ability to perform the following tasks: Document model requirements such as risk rating, intended usage, limitations, and expected performance.

Government 78

Government Metrics APIs Engineering 78

AWS Machine Learning

SEPTEMBER 30, 2022

Security is a big-data problem. It then chooses the hyperparameter values that result in a model that performs the best, as measured by a metric for the given ML task. 24xlarge and x1.32xlarge) to train the model on as large of a sample of the data as possible. The following diagram illustrates the solution architecture.

Scripts 80

Scripts Engineering Metrics Big data 80