AWS Machine Learning

OCTOBER 5, 2023

He holds a PhD in Electrical Engineering from Northwestern University. Karthick has a PhD in Industrial and Systems Engineering with a minor in Operations Research from North Carolina State University. Before joining AWS, he obtained a PhD in Electrical Engineering from Stanford University. He founded StylingAI Inc.,

Scripts 99

Scripts Big data Engineering SaaS 99

AWS Machine Learning

DECEMBER 7, 2023

In this post, we describe how we reduced the modelling time by 70% by doing the feature engineering and modelling using Amazon Forecast. The vast array of models and the sophisticated feature engineering capabilities offered by AWS Forecast proved more advantageous and optimized our resource utilization.

Management 101

Management Engineering Analytics Construction 101

AWS Machine Learning

MARCH 13, 2024

To develop models for such use cases, data scientists need access to various datasets like credit decision engines, customer transactions, risk appetite, and stress testing. Kesaraju Sai Sandeep is a Cloud Engineer specializing in Big Data Services at AWS.

Accountability 90

Accountability Engineering Enterprise Big data 90

AWS Machine Learning

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. Another essential component is an orchestration tool suitable for prompt engineering and managing different type of subtasks. A feature store maintains user profile data.

Personalization 113

Personalization Engineering Construction Transportation 113

Branch Mesenger

MAY 2, 2018

Using Big Data to Make Leadership Advances in the Workplace. Efforts helped Best Buy crimp employee turnover “well into the double digits,” Timothy Embretson, director of retail user experience told the attendees at the Future Stores Miami conference in February of 2018.

Engineering 74

Engineering Morale Employee engagement Big data 74

AWS Machine Learning

FEBRUARY 13, 2024

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

Accountability 106

Accountability Government Engineering Scripts 106

Connect

APRIL 18, 2024

It is costly and complex to build out Gen AI capabilities as creating the modelling needed to derive insights from AI engines is intensive, requiring scarce and expensive resources like data scientists and other technical experts. However, Gen AI is not a plug-and-play solution.

Virtual Agent 74

Virtual Agent Chatbots Average Handle Time Engineering 74

AWS Machine Learning

FEBRUARY 13, 2024

In our entire partnership, AWS has set the bar on customer obsession and delivering results—working with us the whole way to realize promised benefits.” – Keshav Kumar, Head of Engineering at BigBasket. About the Authors Santosh Waddi is a Principal Engineer at BigBasket, brings over a decade of expertise in solving AI challenges.

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Engineering Gamification Scripts Big data 102

Beyond Philosophy

JULY 5, 2016

Create experiences that are proactively human-engineered. Within customer-related processes, experiences need to be designed, engineered, or re-engineered, so that authentic humanity is built in. It is employees who are the real, flexible experience engineers.

Customer Experience 210

Customer Experience Engineering Customer centricity B2C 210

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.

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Scripts Engineering APIs Big data 74

AWS Machine Learning

OCTOBER 30, 2023

He is passionate about building secure and scalable AI/ML and big data solutions to help enterprise customers with their cloud adoption and optimization journey to improve their business outcomes. About the Authors Ram Vittal is a Principal ML Solutions Architect at AWS. With an M.Sc.

APIs 126

APIs Big data Accountability Enterprise 126

AWS Machine Learning

NOVEMBER 29, 2023

The no-code environment of SageMaker Canvas allows us to quickly prepare the data, engineer features, train an ML model, and deploy the model in an end-to-end workflow, without the need for coding. The interactive data preparation enabled quickly cleaning, transforming, and analyzing the loan data to engineer informative features.

Engineering 103

Engineering Big data Customer centricity Education 103

AWS Machine Learning

DECEMBER 12, 2023

Amith (R) Mamidala is the senior machine learning application engineering at AWS Annapurna Labs. After a brief stint as an AI engineer at a financial hedge fund, Dr. Mamidala joined the Annapurna labs focusing on Large Language model training. Dr. Huan works on AI and Data Science. He founded StylingAI Inc.,

Scripts 98

Scripts Engineering Big data Management 98

AWS Machine Learning

NOVEMBER 27, 2023

In summary, RAG based question answering dataflow is as follows: ML practitioners spend a lot of time crafting feature engineering code, applying it to their initial datasets, training models on the engineered datasets, and evaluating model accuracy. Let’s select the + button to the right of the query.

Engineering 75

Engineering APIs Big data Accountability 75

CSM Magazine

JULY 29, 2021

It is the main innovation behind the engine that performs functions such as task prediction and dialog control. Addepto is one of the top data science and AI consulting companies operating in over 12 countries. They typically help businesses make bolder decisions through internet data and AI.

Real estate 98

Real estate Engineering Consulting Consulting 98

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 75

Calibration Engineering Big data Automotive 75

AWS Machine Learning

SEPTEMBER 9, 2022

Our initial ML model uses 21 batch features computed daily using data captured in the past 2 months. This data includes both playback and app engagement history per user, and grows with the number of users and frequency of app usage. Manolya McCormick is a Sr Software Development Engineer for Amp on Amazon. Real-time inference.

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Personalization APIs Engineering Metrics 73

AWS Machine Learning

AUGUST 29, 2022

You can benefit from cross-account sharing of SageMaker pipelines in the following use cases: When data scientists build ML workflows in a dev account, those workflows are then deployed by an ML engineer as a SageMaker pipeline into a dedicated test account. Ram Vittal is an ML Specialist Solutions Architect at AWS.

Accountability 84

Accountability APIs Management Engineering 84

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 124

Best practices Government Engineering Accountability 124

Peter Lavers

JULY 17, 2017

Giant leaps have been made in the disciplines of customer insight that businesses must embrace – Data Science, Big Data, Artificial Intelligence (AI), Cognitive Marketing, etc. Insight dependency and democratisation. And I’m not just talking about your Business Intelligence departments!

Customer Experience 182

Customer Experience Customer centricity Management Automotive 182

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. Data Engineer for Amp on Amazon.

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Analytics Engineering APIs Metrics 70

TechSee

OCTOBER 9, 2018

With big data and advanced analytics readily available, companies can provide Millennials with the acknowledgement they demand. Most top-tier cloud CRM solutions include a self-service engine to manage the knowledge base and help customers solve problems on their own. Pay attention. AI-powered virtual agents.

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Customer Service Self service Virtual Agent Chatbots 359

AWS Machine Learning

AUGUST 8, 2023

Amazon SageMaker offers several ways to run distributed data processing jobs with Apache Spark, a popular distributed computing framework for big data processing. Conclusion In this post, we shared a solution you can use to quickly install the Spark UI on SageMaker Studio.

Scripts 68

Scripts Engineering Big data Management 68

DMG Consulting

AUGUST 17, 2017

Advancements in artificial intelligence (AI), machine learning, Big Data analytics, and mobility are all driving contact center innovation. This Big Data application is intended to track, evaluate, and measure activities and sentiment at every step of the customer journey. Customer journey analytics.

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Contact Center Technology Big data Gamification 69

TechSee

FEBRUARY 1, 2021

This data is culled from devices, networks, mobile applications, geolocations, detailed customer profiles, services usage and billing data. Deutsche Telekom’s chatbot, Tinka , acts as a search engine by providing targeted assistance to customers in Austria (see her at the bottom right of screen).

Telecommunications 107

Telecommunications Chatbots Big data Average Handle Time 107

Natalie Petouhof

JUNE 4, 2015

Key Principle #2: Big Data Technologies: Aster, Hadoop, Big Data Apps, Apps Center, Open Source Contribution and leverage. Key Principle #5: Consulting, Big Data Consulting, Analytics Consulting, Managed Services. Key Principle#3: Cloud for Analytics. Who should lead this?

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Big data Chief Customer Officer Analytics Consulting 53

SharpenCX

OCTOBER 7, 2022

Give your data scientists a tour of your contact center and make sure that they are visible during the project. The product manager wall between the engineers is a very weak link. It’s the data scientists’ responsibility to solve real problems for our customers. We have to rewrite all of our models every time one quits!”

Contact Center 67

Contact Center Contact center software Big data Engineering 67

Hello Customer

JUNE 21, 2023

But what organizations can do is reverse engineer that 11-star experience. Representation of the data flow within Hello Customer For data to be valuable it’s crucial that you can manage, store and use data in an efficient way. That’s where the concept of data mesh comes into play.

Customer Experience 52

Customer Experience Engineering Feedback Finance 52

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 67

APIs Engineering Construction Benchmark 67

JivoChat

FEBRUARY 1, 2023

Online courses for data science can help you keep up to date with the changes that computer engineering and artificial intelligence development have brought up to multiple industries sectors. Workload: 15.5

Big data 75

Big data Chatbots Engineering 75

CustomerSuccessBox

MAY 30, 2022

Just imagine the enormity of untracked data. This data can uncover the underlying intent of the customer. Moreover, the rule engines are not calibrated frequently and as result the signals are false. Only data and NO insights. CS platforms track each and every data point. Based on rule engines.

Upselling 52

Upselling Calibration Engineering Big data 52

Natalie Petouhof

FEBRUARY 1, 2016

Teradata will re-sell the Alation Data Catalog to Teradata customers and prospects struggling to achieve trust in data – in those data environments that have grown more complex with big data. . The Teradata and Alation partnership includes joint engineering, joint sales engagement and joint marketing.

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Self service Analytics Big data Engineering 40

SmartAction

NOVEMBER 4, 2020

It’s also why these same transcription-based engines like a Google or Amazon don’t deliver a good enough customer experience at the contact center level, because they are now 50% less accurate. And, if that wasn’t bad enough, it adds noise. This is why conversational AI over telephony is a really difficult challenge.

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Big data Interactive Voice Response Virtual Agent Scripts 53

CSM Magazine

JUNE 18, 2020

Big Data – Today’s companies are dealing with enormous and diverse amounts of data that require management on a daily basis. The mining of this big data, whether structured or unstructured, requires effective testing processes to help ensure that all information is accurate and usable.

Big data 52

Big data outsourcing Construction Engineering 52

AWS Machine Learning

JULY 19, 2022

He has more than a decade of experience working in a variety of technology roles, with a focus on software engineering and architecture. He helps them drive their cloud architecture and data strategy using best practices. His background is in distributed computing, big data analytics, and data engineering.

Engineering 85

Engineering APIs Education Best practices 85

AWS Machine Learning

OCTOBER 4, 2022

In several domains, ML has proven capable of solving problems previously unsolvable with classical big data and analytical techniques, and the demand for data science and ML practitioners is increasing steadily. We create the following steps: Processing step (feature engineering). Model training and tuning.

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Scripts Engineering Management APIs 73

Natalie Petouhof

AUGUST 15, 2022

With Systems of Listening in place, companies have reliable sources of VoC and VoE data that can fuel customer experience and employee experience analytics, big data analytics engines, and interactive dashboards. And it allows them to truly know what customers (and employees) are doing, saying and feeling.

Customer Experience 52

Customer Experience Analytics Big data Surveys 52