AWS Machine Learning

JULY 24, 2023

as_trt_engine(output_fpath=trt_path, profiles=profiles) gpt2_trt = GPT2TRTDecoder(gpt2_engine, metadata, config, max_sequence_length=42, batch_size=10) Latency comparison: PyTorch vs. TensorRT JMeter is used for performance benchmarking in this project. implement the model and the inference API. model_fp16.onnx gpt2 and predictor.py

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

MARCH 20, 2023

Refer to the appendix for instance details and benchmark data. Quantizing the model in PyTorch is possible with a few APIs from Intel PyTorch extensions. Benchmark data The following table compares the cost and relative performance between c5 and c6 instances. times greater with INT8 quantization. Refer to invoke-INT8.py

Calibration 78

Calibration Scripts Benchmark APIs 78

Comm100

SEPTEMBER 23, 2021

Ensure you find benchmarks and determine prompt response times for your business for the asynchronous communication channels like Facebook, SMS, and email. You can make your customers feel special through controlled APIs, customer segmentation, and user metrics mapping. Personalize Customer Experience.

Customer Service 79

Customer Service Chatbots APIs Benchmark 79

Talkdesk

MAY 31, 2017

This means users can customize their real-time reporting dashboards by selecting which metrics appear and set KPI thresholds for improved benchmarking efforts. Enterprise Plan Users: Reporting API Open Beta. Talkdesk Enterprise plan users can now request access to the Calls Report API or User Status Report API.

APIs 40

APIs Call Center Enterprise Benchmark 40

AWS Machine Learning

DECEMBER 6, 2022

compute metrics function def compute_metrics(pred): targets = 1 * (pred.label_ids >= 0.5) compute metrics function def compute_metrics(pred): targets = 1 * (pred.label_ids >= 0.5) The Trainer class provides an API for feature-complete training in PyTorch. outputs = 1 * (pred.predictions >= 0.5)

Engineering 74

Engineering APIs Construction Metrics 74

ChurnZero

NOVEMBER 5, 2021

To learn how ChurnZero helps customers comply with privacy laws, check out our documentation on ChurnZero’s API for privacy laws compliance. How has your Customer Success software influenced company-wide metrics such as Net Revenue Retention (NRR), Net Promoter Score® (NPS), and Customer Lifetime Value (CLTV)?

Accountability 52

Accountability CRM APIs Benchmark 52

AWS Machine Learning

SEPTEMBER 1, 2023

In this scenario, the generative AI application, designed by the consumer, must interact with the fine-tuner backend via APIs to deliver this functionality to the end-users. If an organization has no AI/ML experts in their team, then an API service might be better suited for them. 15K available FM reference Step 1.

Engineering 105

Engineering Accountability Construction APIs 105

Enghouse Interactive

OCTOBER 21, 2020

As noted in the 2019 Dimension Data Customer Experience (CX) Benchmarking report: 88% of contact center decision-makers expect self-service volumes to increase over the next 12 months. These interactions will become longer – so traditional productivity measurements and benchmarks will no longer be relevant and will have to be redefined.

Self service 76

Self service Contact Center Benchmark Chatbots 76

AWS Machine Learning

NOVEMBER 16, 2023

Enable a data science team to manage a family of classic ML models for benchmarking statistics across multiple medical units. Another important metric is the efficiency for data science users. The data science team expected an AI-based automated image annotation workflow to speed up a time-consuming labeling process.

Healthcare 91

Healthcare Government Engineering APIs 91

AWS Machine Learning

JUNE 29, 2022

This necessitates the requirement for a fully managed service that can be integrated into applications using API calls without the need for extensive machine learning (ML) expertise. Over time, various NLP techniques for text analysis have also evolved. Set up the AWS CLI and AWS SDKs. Optional) Set up your Cloud9 IDE environment.

Metrics 73

Metrics Telecommunications APIs Benchmark 73

ChurnZero

NOVEMBER 5, 2021

To learn how ChurnZero helps customers comply with privacy laws, check out our documentation on ChurnZero’s API for privacy laws compliance. How has your Customer Success software influenced company-wide metrics such as Net Revenue Retention (NRR), Net Promoter Score® (NPS), and Customer Lifetime Value (CLTV)?

Accountability 52

Accountability CRM APIs Benchmark 52

AWS Machine Learning

OCTOBER 5, 2022

The decision tree provided the cut-offs for each metric, which we included as rules-based logic in the streaming application. At the end, we found that the LightGBM model worked best with well-calibrated accuracy metrics. To evaluate the performance of the models, we used multiple techniques.

Calibration 92

Calibration Engineering Automotive Analytics 92

AWS Machine Learning

APRIL 20, 2023

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. An advanced job is a custom load test job that allows you to perform extensive benchmarks based on your ML application SLA requirements, such as latency, concurrency, and traffic pattern.

APIs 79

APIs Metrics Benchmark Engineering 79

AWS Machine Learning

FEBRUARY 8, 2023

Although you can integrate the model directly into an application, the approach that works well for production-grade applications is to deploy the model behind an endpoint and then invoke the endpoint via a RESTful API call to obtain the inference. However, you can use any other benchmarking tool.

Benchmark 76

Benchmark Metrics APIs Engineering 76

AWS Machine Learning

APRIL 22, 2024

Examples of tools you can use to advance sustainability initiatives are: Amazon Bedrock – a fully managed service that provides access to high-performing FMs from leading AI companies through a single API, enabling you to choose the right model for your sustainability use cases.

Best practices 114

Best practices Benchmark Transportation Engineering 114

AWS Machine Learning

FEBRUARY 6, 2023

The former question addresses model selection across model architectures, while the latter question concerns benchmarking trained models against a test dataset. This post provides details on how to implement large-scale Amazon SageMaker benchmarking and model selection tasks. swin-large-patch4-window7-224 195.4M efficientnet-b5 29.0M

APIs 71

APIs Scripts Metrics Benchmark 71

AWS Machine Learning

SEPTEMBER 21, 2023

Use managed services – Depending on your expertise and specific use case, weigh the options between opting for Amazon Bedrock , a serverless, fully managed service that provides access to a diverse range of foundation models through an API, or deploying your models on a fully managed infrastructure by using Amazon SageMaker.

Best practices 102

Best practices Engineering Metrics APIs 102

AWS Machine Learning

JUNE 13, 2023

In addition, all SageMaker real-time endpoints benefit from built-in capabilities to manage and monitor models, such as including shadow variants , auto scaling , and native integration with Amazon CloudWatch (for more information, refer to CloudWatch Metrics for Multi-Model Endpoint Deployments ).

APIs 65

APIs Benchmark Engineering Management 65

AWS Machine Learning

APRIL 8, 2024

In this post, we explore the latest features introduced in this release, examine performance benchmarks, and provide a detailed guide on deploying new LLMs with LMI DLCs at high performance. Before introducing this API, the KV cache was recomputed for any newly added requests.

Engineering 86

Engineering Calibration APIs Enterprise 86

CSM Magazine

JANUARY 11, 2016

APIs can be hooked up and performance metrics and social data can be overlaid with CRM systems for traditional channels. It found there was no benchmark standard and the decision should be driven by use case. Businesses need a robust strategic approach to setting up and evolving customer engagement onsocial channels.

Customer Service 40

Customer Service Contact Center Accountability APIs 40

AWS Machine Learning

NOVEMBER 30, 2023

Customers have to leave their development environment to use academic tools and benchmarking sites, which require highly-specialized knowledge. The sheer number of metrics make it hard to filter down to ones that are truly relevant for their use-cases. The aggregated score is a number between 0 (worst) and 1 (best) for each metric.

Construction 89

Construction Metrics industry standards APIs 89

SmartKarrot

SEPTEMBER 22, 2022

The Net Promoter Score, also known as NPS, is a metric used to measure customer satisfaction (CSAT) and brand advocacy. Once you have a benchmark that can be decided according to the industry you are in, measuring your NPS frequently will help you to monitor and track progress to avoid a high churn rate and improve retention.

Surveys 10

Surveys Feedback Benchmark APIs 10

AWS Machine Learning

JANUARY 19, 2024

The goal of NAS is to find the optimal architecture for a given problem by searching over a large set of candidate architectures using techniques such as gradient-free optimization or by optimizing the desired metrics. The performance of the architecture is typically measured using metrics such as validation loss. training.py ).

Metrics 99

Metrics Scripts Benchmark Enterprise 99

AWS Machine Learning

MAY 9, 2023

In addition, you can now use Application Auto Scaling with provisioned concurrency to address inference traffic dynamically based on target metrics or a schedule. To specify the metrics and target values for a scaling policy, you can configure a target-tracking scaling policy. Define the scaling policy as a JSON block in a text file.

Metrics 67

Metrics Best practices APIs Engineering 67

AWS Machine Learning

JANUARY 10, 2023

From there, we dive into how you can track and understand the metrics and performance of the SageMaker endpoint utilizing Amazon CloudWatch metrics. We first benchmark the performance of our model on a single instance to identify the TPS it can handle per our acceptable latency requirements. Metrics to track.

Best practices 72

Best practices Scripts APIs Metrics 72

AWS Machine Learning

NOVEMBER 22, 2023

Define goals and metrics – The function needs to deliver value to the organization in different ways. Establish regular cadence – The group should come together regularly to review their goals and metrics. This allows the workload to be implemented to achieve the desired goals of the organization.

Finance 82

Finance Best practices APIs Accountability 82

AWS Machine Learning

APRIL 12, 2023

All the training and evaluation metrics were inspected manually from Amazon Simple Storage Service (Amazon S3). For every epoch in our training, we were already sending our training metrics through stdOut in the script. This allows us to compare training metrics like accuracy and precision across multiple runs as shown below.

Scripts 81

Scripts APIs Metrics Best practices 81

Pointillist

JULY 25, 2018

Success Metrics for the Team. Ultimately, the biggest success metric for the Champion is to be able to show the Executive Sponsor and key Stakeholders that real business value has been gained through the use of customer journey analytics. Success Metrics for the Project. Success Metrics for the Business. Churn Rate.

Analytics 93

Analytics Government APIs Metrics 93

AWS Machine Learning

MAY 8, 2023

To use TensorRT as a backend for Triton Inference Server, you need to create a TensorRT engine from your trained model using the TensorRT API. The trtexec tool has three main purposes: Benchmarking networks on random or user-provided input data. For this post, we use the trtexec CLI tool. Generating serialized engines from models.

Engineering 83

Engineering APIs Best practices Scripts 83

ProProfs Blog

DECEMBER 17, 2021

The comprehensive dashboard allows you to gauge completion rate, user data, NPS score trends , and other metrics easily. The “Collect, Contextualise and Communicate” approach allows you to effectively capture feedback without interrupting users via in-app feedback widgets and APIs. Product Feedback. Content Feedback. Source: Mopinion.

Feedback 78

Feedback Surveys APIs Customer centricity 78

CallSource Insights

OCTOBER 3, 2018

If your website has a lot of indexed public facing pages, then this metric might matter a lot more. Site load can vary from pages loading, resources downloading, videos buffering, API calls or requests being made, etc. Audience > Benchmarking > Devices. Audience > Benchmarking > Channels.

Analytics 70

Analytics Benchmark APIs Metrics 70

AWS Machine Learning

SEPTEMBER 20, 2022

As is explained in the post Amazon SageMaker JumpStart models and algorithms now available via API , the following artifacts are required to train a pre-built algorithm via the SageMaker SDK: Its framework-specific container image, containing all the required dependencies for training and inference. . Benchmarking the trained models.

Scripts 69

Scripts Metrics Telecommunications APIs 69

AWS Machine Learning

JUNE 9, 2023

The pre-trained GNN embeddings show a 24% improvement on a shopper activity prediction task over a state-of-the-art BERT- based baseline; it also exceeds benchmark performance in other ads applications.” Basically, by using the API of this layer, you can focus on the model development without worrying about how to scale the model training.

Enterprise 87

Enterprise Construction Engineering Metrics 87

AWS Machine Learning

JUNE 9, 2023

Furthermore, we benchmark the ResNet50 model and see the performance benefits that ONNX provides when compared to PyTorch and TensorRT versions of the same model, using the same input. The testing benchmark results are as follows: PyTorch – 176 milliseconds, cold start 6 seconds TensorRT – 174 milliseconds, cold start 4.5 seconds to 1.61

Benchmark 90

Benchmark Engineering Enterprise APIs 90

AWS Machine Learning

OCTOBER 6, 2022

Training and validation loss is just one of the metrics needed to pick the best model for the use case. We trained this model from scratch with the default hyperparameters, so we could have a benchmark to evaluate the rest of the models. Automatic model tuning will monitor the log and parse the objective metrics.

Metrics 82

Metrics APIs Benchmark Accountability 82

AWS Machine Learning

DECEMBER 1, 2022

They show the usage of various SageMaker and JumpStart APIs. This notebook demonstrates how to deploy AlexaTM 20B through the JumpStart API and run inference. This dataset has been widely used as a topic modeling benchmark. They offer a technical solution that you can further customize based on your own needs.

APIs 89

APIs Benchmark Advertising Banking 89