Big data and Scripts - Customer Contact Central

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

OCTOBER 31, 2024

Run the script init-script.bash : chmod u+x init-script.bash./init-script.bash init-script.bash This script prompts you for the following: The Amazon Bedrock knowledge base ID to associate with your Google Chat app (refer to the prerequisites section). The script deploys the AWS CDK project in your account.

APIs

APIs Scripts Accountability Construction

Fine-tune and deploy a summarizer model using the Hugging Face Amazon SageMaker containers bringing your own script

AWS Machine Learning

JULY 29, 2022

Build your training script for the Hugging Face SageMaker estimator. script to use with Script Mode and pass hyperparameters for training. Thanks to our custom inference script hosted in a SageMaker endpoint, we can generate several summaries for this review with different text generation parameters. If we use an ml.g4dn.16xlarge

Scripts

Scripts APIs Big data Engineering

Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

AWS Machine Learning

NOVEMBER 22, 2024

Challenges in data management Traditionally, managing and governing data across multiple systems involved tedious manual processes, custom scripts, and disconnected tools. This approach was not only time-consuming but also prone to errors and difficult to scale.

Government

Government Banking Accountability Engineering

Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium

AWS Machine Learning

OCTOBER 5, 2023

We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw. For example, to use the RedPajama dataset, use the following command: wget [link] python nemo/scripts/nlp_language_modeling/preprocess_data_for_megatron.py

Scripts

Scripts Big data Engineering SaaS

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

NOVEMBER 14, 2024

from time import gmtime, strftime experiment_suffix = strftime('%d-%H-%M-%S', gmtime()) experiment_name = f"credit-risk-model-experiment-{experiment_suffix}" The processing script creates a new MLflow active experiment by calling the mlflow.set_experiment() method with the experiment name above. fit_transform(y).

Government

Government Management APIs Accountability

How Twilio used Amazon SageMaker MLOps pipelines with PrestoDB to enable frequent model retraining and optimized batch transform

AWS Machine Learning

JUNE 17, 2024

Batch transform The batch transform pipeline consists of the following steps: The pipeline implements a data preparation step that retrieves data from a PrestoDB instance (using a data preprocessing script ) and stores the batch data in Amazon Simple Storage Service (Amazon S3).

Scripts

Scripts Engineering Metrics Big data

Use Snowflake as a data source to train ML models with Amazon SageMaker

AWS Machine Learning

MARCH 8, 2023

We create a custom training container that downloads data directly from the Snowflake table into the training instance rather than first downloading the data into an S3 bucket. 1 with the following additions: The Snowflake Connector for Python to download the data from the Snowflake table to the training instance.

Scripts

Scripts Accountability Enterprise Management

Automate Amazon SageMaker Pipelines DAG creation

AWS Machine Learning

FEBRUARY 29, 2024

You can then iterate on preprocessing, training, and evaluation scripts, as well as configuration choices. framework/createmodel/ – This directory contains a Python script that creates a SageMaker model object based on model artifacts from a SageMaker Pipelines training step. script is used by pipeline_service.py The model_unit.py

Scripts

Scripts Engineering Metrics Best practices

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning

NOVEMBER 9, 2023

Under Advanced Project Options , for Definition , select Pipeline script from SCM. For Script Path , enter Jenkinsfile. upload_file("pipelines/train/scripts/raw_preprocess.py","mammography-severity-model/scripts/raw_preprocess.py") s3_client.Bucket(default_bucket).upload_file("pipelines/train/scripts/evaluate_model.py","mammography-severity-model/scripts/evaluate_model.py")

Scripts

Scripts Accountability Best practices Engineering

Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

DECEMBER 21, 2022

SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Customers can also access offline store data using a Spark runtime and perform big data processing for ML feature analysis and feature engineering use cases. Table formats provide a way to abstract data files as a table.

Scripts

Scripts Engineering APIs Big data

21 Business Analysts & Call Center Leaders Reveal the Optimal Role of the Business Analyst in Call Center Operations

Callminer

SEPTEMBER 14, 2020

The business analyst’s role is to evaluate the customer experience and then identify how to improve the customer experience either with software changes or call center script changes. They can assess how current scripts are performing and change them as needed. There would be no operations without customers.

Call Center

Call Center Analytics First call resolution Metrics

Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

AWS Machine Learning

DECEMBER 12, 2023

After downloading the latest Neuron NeMo package, use the provided neox and pythia pre-training and fine-tuning scripts with optimized hyper-parameters and execute the following for a four node training. Before joining AWS, he worked at Baidu research as a distinguished scientist and the head of Baidu Big Data Laboratory.

Scripts

Scripts Engineering Big data Management

Why Businesses Should Hire Cloud Developers: Key Benefits and Best Practices

CSM Magazine

MARCH 24, 2025

A Harvard Business Review study found that companies using big data analytics increased profitability by 8%. While this statistic specifically addresses data-centric strategies, it highlights the broader value of well-structured technical investments.

Best practices

Best practices Analytics Finance Big data

Contact Center Trends 2024: Our Predictions

Fonolo

DECEMBER 8, 2023

We live in an era of big data, AI, and automation, and the trends that matter in CX this year begin with the abilities – and pain points – ushered in by this technology. For example, big data makes things like hyper-personalized customer service possible, but it also puts enormous stress on data security.

Contact Center

Contact Center Big data Chatbots Scripts

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

AWS Machine Learning

MARCH 23, 2023

default_bucket() upload _path = f"training data/fhe train.csv" boto3.Session().resource("s3").Bucket To see more information about natively supported frameworks and script mode, refer to Use Machine Learning Frameworks, Python, and R with Amazon SageMaker. resource("s3").Bucket Bucket (bucket).Object Object (upload path).upload

Scripts

Scripts APIs Government Analytics

Customer Experience Automation: Transforming the Future of Customer Service

TechSee

AUGUST 7, 2024

Today, CXA encompasses various technologies such as AI, machine learning, and big data analytics to provide personalized and efficient customer experiences. The development of chatbots, automated email responses, and AI-driven customer support tools marked a new era in customer service automation.

Customer Experience

Customer Experience Customer Service Interactive Voice Response Chatbots

Generate images from text with the stable diffusion model on Amazon SageMaker JumpStart

AWS Machine Learning

NOVEMBER 7, 2022

We first fetch any additional packages, as well as scripts to handle training and inference for the selected task. You can use any number of models pre-trained on the same task with a single inference script. Finally, the pre-trained model artifacts are separately fetched with model_uris , which provides flexibility to the platform.

APIs

APIs Scripts Enterprise Big data

Host the Spark UI on Amazon SageMaker Studio

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. install-scripts chmod +x install-history-server.sh./install-history-server.sh script and attach it to an existing SageMaker Studio domain.

Scripts

Scripts Engineering Big data Management

Guest Blog: Contact Center Talent in These Changing Times, Part 1 – Setting the Stage

Calabrio

NOVEMBER 25, 2020

The one-size-fit-all script no longer cuts it. Technology is also creating new opportunities for contact centers to not only better serve customers but also gain deep insights through Big Data. With analytics, contact centers can leverage their data to see trends, understand preferences and even predict future requirements.

Contact Center

Contact Center Self service Banking Analytics

Four approaches to manage Python packages in Amazon SageMaker Studio notebooks

AWS Machine Learning

MARCH 7, 2023

When you open a notebook in Studio, you are prompted to set up your environment by choosing a SageMaker image, a kernel, an instance type, and, optionally, a lifecycle configuration script that runs on image startup. The main benefit is that a data scientist can choose which script to run to customize the container with new packages.

Management

Management Scripts Government Engineering

Video auto-dubbing using Amazon Translate, Amazon Bedrock, and Amazon Polly

AWS Machine Learning

JULY 15, 2024

We use the custom terminology dictionary to compile frequently used terms within video transcription scripts. Yaoqi Zhang is a Senior Big Data Engineer at Mission Cloud. Adrian Martin is a Big Data/Machine Learning Lead Engineer at Mission Cloud. Here’s an example.

Engineering

Engineering Entertainment Big data APIs

Reduce cost and development time with Amazon SageMaker Pipelines local mode

AWS Machine Learning

OCTOBER 4, 2022

Developers usually test their processing and training scripts locally, but the pipelines themselves are typically tested in the cloud. One of the main drivers for new innovations and applications in ML is the availability and amount of data along with cheaper compute options. Build your pipeline.

Scripts

Scripts Engineering Management APIs

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

AWS Machine Learning

AUGUST 29, 2023

Data I/O design SageMaker interacts directly with Amazon S3 for reading inputs and storing outputs of individual steps in the training and inference pipelines. The pipeline will automatically upload Python scripts from the GitLab repository and store output files or model artifacts from each step in the appropriate S3 path.

Scripts

Scripts APIs Enterprise Accountability

Deploy a Slack gateway for Amazon Bedrock

AWS Machine Learning

JUNE 19, 2024

About the Authors Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice. He helps customers implement big data, machine learning, analytics solutions, and generative AI solutions. To learn more about how to use generative AI with AWS services, see Generative AI on AWS.

APIs

APIs Engineering Accountability Big data

The State of the Bot Going Into 2018

Aspect

DECEMBER 27, 2017

Accordingly, I expect to see a range of new solutions see the light of day in 2018; solutions that bring the old solutions like Interactive Voice Response (cue the robotic ‘press 1 for English’ script) into the 21 st century, on a channel people actually like to use.

Chatbots

Chatbots Contact Center Interactive Voice Response Enterprise

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning

MARCH 15, 2024

To create these packages, run the following script found in the root directory: /build_mlops_pkg.sh He entered the big data space in 2013 and continues to explore that area. Her specialization is machine learning, and she is actively working on designing solutions using various AWS ML, big data, and analytics offerings.

Healthcare

Healthcare Big data Engineering Accountability

Run image segmentation with Amazon SageMaker JumpStart

AWS Machine Learning

AUGUST 26, 2022

We fetch any additional packages, as well as scripts to handle training and inference for the selected task. You can use any number of models pre-trained for the same task with a single training or inference script. Fine-tune the pre-trained model. He’s passionate about building AI services for computer vision.

APIs

APIs Scripts Enterprise Big data

Run text generation with GPT and Bloom models on Amazon SageMaker JumpStart

AWS Machine Learning

NOVEMBER 7, 2022

We first fetch any additional packages, as well as scripts to handle training and inference for the selected task. You can use any number of models pre-trained on the same task with a single inference script. Finally, the pre-trained model artifacts are separately fetched with model_uris , which provides flexibility to the platform.

APIs

APIs Scripts Enterprise Big data

Developing advanced machine learning systems at Trumid with the Deep Graph Library for Knowledge Embedding

AWS Machine Learning

JULY 25, 2022

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.

Scripts

Scripts Engineering Analytics APIs

Perform generative AI-powered data prep and no-code ML over any size of data using Amazon SageMaker Canvas

AWS Machine Learning

AUGUST 15, 2024

Organizations often struggle to extract meaningful insights and value from their ever-growing volume of data. You need data engineering expertise and time to develop the proper scripts and pipelines to wrangle, clean, and transform data. He has a background in AI/ML & big data.

Enterprise

Enterprise Metrics Analytics Big data

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

AWS Machine Learning

DECEMBER 18, 2023

The triggers need to be scheduled to write the data to S3 at a period frequency based on the business need for training the models. Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem.

Finance

Finance APIs Analytics Big data

Optimize for sustainability with Amazon CodeWhisperer

AWS Machine Learning

NOVEMBER 8, 2023

Amazon CodeWhisperer currently supports Python, Java, JavaScript, TypeScript, C#, Go, Rust, PHP, Ruby, Kotlin, C, C++, Shell scripting, SQL, and Scala. times more energy efficient than the median of surveyed US enterprise data centers and up to 5 times more energy efficient than the average European enterprise data center.

Analytics

Analytics Enterprise Big data Scripts

Build a custom UI for Amazon Q Business

AWS Machine Learning

JUNE 12, 2024

You can also find the script on the GitHub repo. He helps organizations in achieving specific business outcomes by using data and AI, and accelerating their AWS Cloud adoption journey. He has extensive experience across big data, data science, and IoT, across consulting and industrials.

APIs

APIs Enterprise Accountability Feedback

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

FEBRUARY 13, 2024

The second script accepts the AWS RAM invitations to discover and access cross-account feature groups from the owner level. His expertise spans a broad spectrum, encompassing scalable architectures, distributed computing, big data analytics, micro services and cloud infrastructures for organizations.

Accountability

Accountability Government Engineering Scripts

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

AWS Machine Learning

APRIL 11, 2023

Populate the data Run the following script to populate the DynamoDB tables and Amazon Cognito user pool with the required information: /scripts/setup/fill-data.sh The script performs the required API calls using the AWS Command Line Interface (AWS CLI) and the previously configured parameters and profiles.

APIs

APIs Accountability Scripts Enterprise

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

AWS Machine Learning

FEBRUARY 13, 2024

During each training iteration, the global data batch is divided into pieces (batch shards) and a piece is distributed to each worker. Each worker then proceeds with the forward and backward pass defined in your training script on each GPU.

Engineering

Engineering Gamification Big data Scripts

11 Contact Center Technologies to Boost Customer Satisfaction

TechSee

DECEMBER 5, 2017

TechSee’s technology combines AI with deep machine learning, proprietary algorithms, and Big Data to deliver a scalable cognitive system that becomes smarter with every customer support interaction. Customers answer questions in a simple Q&A format, which in many cases leads to a problem solution.

Contact Center

Contact Center Technology Self service Call Center

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

FEBRUARY 29, 2024

Before you can write scripts that use the Amazon Bedrock API, you’ll need to install the appropriate version of the AWS SDK in your environment. His expertise is in building Big Data and AI-powered solutions to customer problems especially in biomedical, life sciences and healthcare domain. Nihir Chadderwala is a Sr.

APIs

APIs Healthcare Scripts Enterprise

Machine learning with decentralized training data using federated learning on Amazon SageMaker

AWS Machine Learning

AUGUST 22, 2023

The notebook instance client starts a SageMaker training job that runs a custom script to trigger the instantiation of the Flower client, which deserializes and reads the server configuration, triggers the training job, and sends the parameters response. script and a utils.py The client.py We use utility functions in the utils.py

Scripts

Scripts Accountability Transportation Benchmark

Top 30 Customer Service Books Every Team Needs to Read

Comm100

SEPTEMBER 22, 2016

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. Free Download] Live Chat Scripts to Make Stellar Agents. Loyalty 3.0:

Customer Service

Customer Service Gamification Consulting Consulting

Why Terminator Will Never Really Nail Customer Success

Amity

AUGUST 29, 2016

We are also seeing the influx of big data and the switch to mobile. These are the innate functional limitations of every non-human "system" Namely, no matter how advanced a piece of customer service software is, there are always situations in which its script is not able to make certain leaps that biology is capable of.

CRM

CRM Self service Analytics Big data

Breaking Big: Teradata Believes We are in the Internet of Analytics vs #IOT

Natalie Petouhof

OCTOBER 20, 2015

Teradata Listener is intelligent, self-service software with real-time “listening ” capabilities to follow multiple streams of sensor and IoT data wherever it exists globally, and then propagate the data into multiple platforms in an analytical ecosystem. Teradata Integrated Big Data Platform 1800.

Analytics

Analytics Big data Self service Healthcare

How Sophos trains a powerful, lightweight PDF malware detector at ultra scale with Amazon SageMaker

AWS Machine Learning

SEPTEMBER 30, 2022

Security is a big-data problem. As soon as a download attempt is made, it triggers the malicious executable script to connect to the attacker’s Command and Control server. With the built-in algorithm for XGBoost , you can do this without any additional custom script.

Scripts

Scripts Engineering Metrics Big data

6 Online Data Analyst Courses

JivoChat

JANUARY 31, 2023

The Data Analyst Course With the Data Analyst Course, you will be able to become a professional in this area, developing all the necessary skills to succeed in your career. The course also teaches beginner and advanced Python, basics and advanced NumPy and Pandas, and data visualization.

Analytics

Analytics APIs Big data Scripts

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

Fine-tune and deploy a summarizer model using the Hugging Face Amazon SageMaker containers bringing your own script

Trending Sources

Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

How Twilio used Amazon SageMaker MLOps pipelines with PrestoDB to enable frequent model retraining and optimized batch transform

Use Snowflake as a data source to train ML models with Amazon SageMaker

Automate Amazon SageMaker Pipelines DAG creation

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

21 Business Analysts & Call Center Leaders Reveal the Optimal Role of the Business Analyst in Call Center Operations

Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

Why Businesses Should Hire Cloud Developers: Key Benefits and Best Practices

Contact Center Trends 2024: Our Predictions

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

Customer Experience Automation: Transforming the Future of Customer Service

Generate images from text with the stable diffusion model on Amazon SageMaker JumpStart

Host the Spark UI on Amazon SageMaker Studio

Guest Blog: Contact Center Talent in These Changing Times, Part 1 – Setting the Stage

Four approaches to manage Python packages in Amazon SageMaker Studio notebooks

Video auto-dubbing using Amazon Translate, Amazon Bedrock, and Amazon Polly

Reduce cost and development time with Amazon SageMaker Pipelines local mode

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

Deploy a Slack gateway for Amazon Bedrock

The State of the Bot Going Into 2018

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

Run image segmentation with Amazon SageMaker JumpStart

Run text generation with GPT and Bloom models on Amazon SageMaker JumpStart

Developing advanced machine learning systems at Trumid with the Deep Graph Library for Knowledge Embedding

Perform generative AI-powered data prep and no-code ML over any size of data using Amazon SageMaker Canvas

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

Optimize for sustainability with Amazon CodeWhisperer

Build a custom UI for Amazon Q Business

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

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

11 Contact Center Technologies to Boost Customer Satisfaction

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

Machine learning with decentralized training data using federated learning on Amazon SageMaker

Top 30 Customer Service Books Every Team Needs to Read

Why Terminator Will Never Really Nail Customer Success

Breaking Big: Teradata Believes We are in the Internet of Analytics vs #IOT

How Sophos trains a powerful, lightweight PDF malware detector at ultra scale with Amazon SageMaker

6 Online Data Analyst Courses

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Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction