AWS Machine Learning

OCTOBER 20, 2023

Governing ML lifecycle at scale is a framework to help you build an ML platform with embedded security and governance controls based on industry best practices and enterprise standards. Data scientists create and share new features into the central feature store catalog for reuse.

Government 130

Government Engineering Accountability Enterprise 130

AWS Machine Learning

FEBRUARY 28, 2024

Third, despite the larger adoption of centralized analytics solutions like data lakes and warehouses, complexity rises with different table names and other metadata that is required to create the SQL for the desired sources. Athena also allows us to use a multitude of supported endpoints and connectors to cover a large set of data sources.

Engineering 136

Engineering Best practices Analytics Enterprise 136

AWS Machine Learning

MARCH 18, 2025

Audio-to-text transcription The recorded audio files are securely transmitted to a speech-to-text engine, which converts the spoken words into text format. They provide feedback, make necessary modifications, and enforce compliance with relevant guidelines and best practices.

Healthcare 84

Healthcare Analytics Consulting Consulting 84

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. Ray Khorsandi is an AI/ML specialist at AWS, supporting strategic customers with AI/ML best practices. With an M.Sc.

APIs 141

APIs Big data Accountability Enterprise 141

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 137

Personalization Engineering Construction Transportation 137

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. ” – O. Litomisky, S.

Big data 140

Big data Analytics Metrics Sales 140

TechSee

APRIL 3, 2018

While people and processes continue to play an essential role in reducing customer churn , the technological advancement associated with AI, Big Data analytics, visualization, voice analytics, and other advanced technologies that improve the customer experience offer a critical boost to the human factor.

Customer retention 141

Customer retention Technology Analytics Technical Support 141

DMG Consulting

AUGUST 17, 2017

Advancements in artificial intelligence (AI), machine learning, Big Data analytics, and mobility are all driving contact center innovation. The success of speech analytics demonstrates how good technology accompanied by best practices is a winning formula for companies that can afford the investment.

Contact Center 69

Contact Center Technology Big data Gamification 69

ClearAction

APRIL 18, 2015

Use group sharing engines to share documents with strategies and knowledge across departments. Create CX playbooks & best practice to guide interactions with customers. Data can be insightful to all of the roles HR takes on in facilitating the company’s CX goals. Here are ways HR can help: Knowledge Management.

Customer Experience 96

Customer Experience Employee engagement Big data Customer centricity 96

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. Jinzhao Feng , is a Machine Learning Engineer at AWS Professional Services.

Scripts 121

Scripts Engineering Metrics Best practices 121

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 118

Accountability Engineering Enterprise Big data 118

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 96

Engineering Analytics Self service Government 96

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.

Personalization 92

Personalization APIs Metrics Engineering 92

ConvergeOne

DECEMBER 7, 2021

The underlying technologies of composability include some combination of artificial intelligence (AI), machine learning, automation, container-based architecture, big data, analytics, low-code and no-code development, Agile/DevOps deployment, cloud delivery, and applications with open APIs (microservices).

APIs 79

APIs Big data Analytics Self service 79

AWS Machine Learning

AUGUST 31, 2023

In addition to data engineers and data scientists, there have been inclusions of operational processes to automate & streamline the ML lifecycle. He is a builder who enjoys helping customers accomplish their business needs and solve complex challenges with AWS solutions and best practices.

Government 120

Government Accountability Enterprise Best practices 120

AWS Machine Learning

JUNE 3, 2024

Prepare your data As expected in the ML process, your dataset may require transformations to address issues such as missing values, outliers, or perform feature engineering prior to model building. SageMaker Canvas provides ML data transforms to clean, transform, and prepare your data for model building without having to write code.

Surveys 119

Surveys Metrics Engineering Analytics 119

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.

Analytics 89

Analytics Engineering Metrics APIs 89

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. tar czvf model.tar.gz -C deepspeed.

Management 117

Management Best practices APIs Calibration 117

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 works with AWS EdTech customers, guiding them with architectural best practices for migrating existing workloads to the cloud and designing new workloads with a cloud-first approach.

Engineering 98

Engineering APIs Education Best practices 98

AWS Machine Learning

DECEMBER 14, 2023

ICL is a multi-national manufacturing and mining corporation based in Israel that manufactures products based on unique minerals and fulfills humanity’s essential needs, primarily in three markets: agriculture, food, and engineered materials. He was fortunate to research spatial and time series data in the precision agriculture domain.

Engineering 108

Engineering Big data outsourcing Education 108

Cincom

JANUARY 31, 2025

Companies use advanced technologies like AI, machine learning, and big data to anticipate customer needs, optimize operations, and deliver customized experiences. Creating robust data governance frameworks and employing tools like machine learning, businesses tend derive actionable insights to achieve a competitive edge.

CRM 40

CRM Analytics Automotive Technology 40

AWS Machine Learning

JUNE 25, 2024

With over 35 patents granted across various technology domains, she has a passion for continuous innovation and using data to drive business outcomes. Shelbee is a co-creator and instructor of the Practical Data Science specialization on Coursera. She is also the Co-Director of Women In Big Data (WiBD), Denver chapter.

Metrics 120

Metrics APIs Government Big data 120

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 122

Scripts Accountability Best practices Engineering 122

AWS Machine Learning

MARCH 23, 2023

To learn more about real-time endpoint architectural best practices, refer to Creating a machine learning-powered REST API with Amazon API Gateway mapping templates and Amazon SageMaker. We perform data exploration and feature engineering using a SageMaker notebook, and then perform model training using a SageMaker training job.

Scripts 117

Scripts APIs Government Analytics 117

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 87

Scripts Engineering Big data Management 87

AWS Machine Learning

SEPTEMBER 9, 2022

Consequently, maintaining and augmenting older projects required more engineering time and effort. In addition, as new data scientists joined the team, knowledge transfers and onboarding took more time, because synchronizing local environments included many undocumented dependencies.

Engineering 95

Engineering Healthcare APIs Scripts 95

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 86

APIs Engineering Construction Benchmark 86

Natalie Petouhof

AUGUST 26, 2015

Prior to starting Totango, he worked in the area of real-time Big Data as executive vice president of engineering at GigaSpaces Technologies, a middleware provider. Today, it maintains two offices, one in San Mateo, California and one in Tel Aviv, Israel. Guy Nirpaz leads the company as CEO and co-founder.

Sales 51

Sales Management Advertising Best practices 51

AWS Machine Learning

AUGUST 29, 2023

Refer to Operating model for best practices regarding a multi-account strategy for ML. The data engineer is responsible for the following: Uploading labeled training data to the appropriate path in Amazon S3. Vivek Lakshmanan is a Machine Learning Engineer at Amazon.

Scripts 93

Scripts APIs Enterprise Accountability 93

REVE Chat Blog

FEBRUARY 12, 2020

Make use of big data analytics. This includes taking a 360-degree view of your banking customer and leveraging the data available. . Big data analytics is a vital ingredient in enhancing customer experience in banking and making crucial business decisions. What obstacles might they face? .

Banking 76

Banking Customer Experience Chatbots Big data 76

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

AUGUST 2, 2023

The image repository is then indexed by Amazon Kendra, which is a search engine that can be used to search for structured and unstructured data. About the Authors Charalampos Grouzakis is a Data Scientist within AWS Professional Services. Tanvi Singhal is a Data Scientist within AWS Professional Services.

Enterprise 91

Enterprise Healthcare APIs Big data 91

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. To improve productivity, all the required parts and correct tools need to be available for the engineers at each stage of production. Edge computing.

Transportation 95

Transportation APIs Big data Wireless 95

AWS Machine Learning

APRIL 24, 2023

With 8 years of experience in the IT industry, Ray is dedicated to building modern solutions on the cloud, especially in NoSQL, big data, and machine learning. Before joining AWS, she was a software engineer. About the Authors Ray Wang is a Solutions Architect at AWS. He loves to read and watch sci-fi movies in his spare time.

Customer Experience 78

Customer Experience APIs Feedback Chatbots 78

Calabrio

APRIL 25, 2017

Traditionally contact centers have been dealing with two main data challenges. Real-time data. Real-time data is handled by a separate, dedicated real-time engine that feeds a set of separate reports. The birth of Big Data. Today there are technologies that are capable of handling large quantities of data.

Multichannel 40

Multichannel Contact Center Big data Metrics 40

ConvergeOne

DECEMBER 7, 2021

The underlying technologies of composability include some combination of artificial intelligence (AI), machine learning, automation, container-based architecture, big data, analytics, low-code and no-code development, Agile/DevOps deployment, cloud delivery, and applications with open APIs (microservices).

APIs 40

APIs Big data Analytics Self service 40

AWS Machine Learning

DECEMBER 1, 2022

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. An example IAM policy for an ML administrator may look like the following code.

Management 93

Management Government Enterprise APIs 93