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

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

JustCall

APRIL 18, 2023

Based on these metrics, you can make data-aware decisions regarding which leads require a follow-up and when. JustCall IQ is a key proposition of JustCall, enabling call centers with AI capabilities that fuel their sales metrics and set newer benchmarks. Recommended Read: What is Conversation Intelligence?

call center software 52

call center software Call Center call center solutions Enterprise 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. Some models may be trained on diverse text datasets like internet data, coding scripts, instructions, or human feedback. 15K available FM reference Step 1.

Engineering 101

Engineering Accountability Construction APIs 101

JustCall

MARCH 9, 2023

After the software processes all this data, it can generate reports on sales performance metrics like sentiment, buying moments, call conversions, revenue from calls, average deal size, and more. Dialogue Scripting for a Seamless User Experience and Empathy Good conversations require so much more than just a simple response.

Coaching 52

Coaching Sales Chatbots Analytics 52

Pointillist

JULY 25, 2018

Success Metrics for the Team Champion – It is important for the champion to understand thoroughly the value of customer journey analytics as an analytics platform and believe that the regular users have built proficiency to use the platform meaningfully on a regular basis. Pick a mix of financial, customer and operational metrics.

Analytics 43

Analytics Metrics Government Journey mapping 43

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

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 95

Metrics Scripts Benchmark Enterprise 95

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

APRIL 12, 2023

All the training and evaluation metrics were inspected manually from Amazon Simple Storage Service (Amazon S3). The code to invoke the pipeline script is available in the Studio notebooks, and we can change the hyperparameters and input/output when invoking the pipeline.

Scripts 79

Scripts APIs Metrics Best practices 79

AWS Machine Learning

JUNE 6, 2023

The following figure shows a performance benchmark of fine-tuning a RoBERTa model on Amazon EC2 p4d.24xlarge inference with AWS Graviton processors for details on AWS Graviton-based instance inference performance benchmarks for PyTorch 2.0. Run your DLC container with a model training script to fine-tune the RoBERTa model.

Scripts 69

Scripts APIs Benchmark Management 69

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. script from the following cell. For this post, we use the trtexec CLI tool.

Engineering 83

Engineering APIs Best practices Scripts 83

AWS Machine Learning

NOVEMBER 29, 2023

Each trained model needs to be benchmarked against many tasks not only to assess its performances but also to compare it with other existing models, to identify areas that needs improvements and finally, to keep track of advancements in the field. Furthermore, these data and metrics must be collected to comply with upcoming regulations.

Benchmark 82

Benchmark Metrics Engineering APIs 82