DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. This may be accomplished through a wide variety of tests, to develop a deeper introspection into how the model behaves.

Risk 52

Risk Modeling Metrics Business Objectives 52

DataRobot

JUNE 10, 2021

To foster innovation in this area, AICrowd hosted a competition to predict the olfactory properties of a molecule. If machine learning could contribute, this would allow for the faster invention of new compounds tailored for particular aromatic signatures. The best model for this dataset is a Keras-based neural network.

Metrics 52

Metrics Machine Learning Visualization Experimentation 52

IBM Big Data Hub

AUGUST 16, 2023

The organization should also decide which cloud service type to utilize from three different options: IaaS (Infrastructure-as-a-Service) provides on-demand access to cloud-hosted physical and virtual servers, storage and networking—the backend IT infrastructure for running applications and workloads in the cloud.

Cost-Benefit 70

Cost-Benefit Data Processing Optimization Software 70

AWS Big Data

MAY 2, 2023

If your updates to a dataset triggers multiple subsequent DAGs, then you can use the Airflow metric max_active_tasks_per_dag to control the parallelism of the consumer DAG and reduce the chance of overloading the system. The workflow steps are as follows: The producer DAG makes an API call to a publicly hosted API to retrieve data.

Testing 103

Testing Experimentation Management Metadata 103

AWS Big Data

JANUARY 9, 2024

2023 was a year of rapid innovation within the artificial intelligence (AI) and machine learning (ML) space, and search has been a significant beneficiary of that progress. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space to find matches.

Cost-Benefit 95

Cost-Benefit Visualization Modeling Machine Learning 95

DataRobot

JANUARY 15, 2020

Kaggle is a popular online forum that hosts machine learning competitions with real-world data, often provided by commercial or non-profit enterprises to crowd-source AI solutions to their problems. For every competition, the host provides a training and test set of data.

Data Processing 16

Data Processing Testing Metrics Machine Learning 16

DataKitchen

APRIL 13, 2021

Testing and Data Observability. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 307

Testing Machine Learning Consulting Data Quality 307

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

AWS Big Data

MARCH 13, 2024

RAG is a machine learning (ML) architecture that uses external documents (like Wikipedia) to augment its knowledge and achieve state-of-the-art results on knowledge-intensive tasks. Each service implements k-nearest neighbor (k-NN) or approximate nearest neighbor (ANN) algorithms and distance metrics to calculate similarity.

Data Processing 114

Data Processing Dashboards Machine Learning Management 114

DataKitchen

NOVEMBER 29, 2021

Model developers will test for AI bias as part of their pre-deployment testing. Quality test suites will enforce “equity,” like any other performance metric. Continuous testing, monitoring and observability will prevent biased models from deploying or continuing to operate. Companies Commit to Remote.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

O'Reilly on Data

JANUARY 17, 2023

” If none of your models performed well, that tells you that your dataset–your choice of raw data, feature selection, and feature engineering–is not amenable to machine learning. All of this leads us to automated machine learning, or autoML. Is autoML the bait for long-term model hosting?

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

IBM Big Data Hub

NOVEMBER 13, 2023

Kubernetes can also run on bare metal servers and virtual machines (VMs) in private cloud, hybrid cloud and edge settings, provided the host OS is a version of Linux or Windows. Overall, Kubernetes provides the flexibility, portability and scalability needed to train, test, schedule and deploy ML and generative AI models.

Machine Learning 119

Machine Learning Data-driven Software Testing 119

IBM Big Data Hub

APRIL 8, 2024

  Db2 Warehouse , our cloud-native data warehouse for real-time operational analytics, business intelligence (BI), reporting and machine learning (ML), is also available as a fully managed service on AWS to support customer’s data warehousing needs.    Scalability 5. Database management, monitoring and tools 14.

Snapshot 78

Snapshot Data Warehouse Data Processing Management 78

CIO Business Intelligence

AUGUST 15, 2023

In partnership with OpenAI and Microsoft, CarMax worked to develop, test, and iterate GPT-3 natural language models aimed at achieving those results. And it yields multiple business metric improvements, such as limiting surplus inventory. They turned to artificial intelligence to help.

IT 98

IT Manufacturing IoT Cost-Benefit 98

The Unofficial Google Data Science Blog

JULY 17, 2018

Often such decisions are the responsibility of a separate machine learning (ML) system. Alternatively, guidance and insight may be delivered below the executive level to product managers and engineering leads, directing product feature development via metrics and A/B experiments.

Data Science 85

Data Science Snapshot Data Processing Optimization 85

Cloudera

FEBRUARY 28, 2024

This property specifies the cluster that the SRM service role will gather replication metrics from (i.e. This can be done using the kafka-producer-perf-test CLI tool. Using SSH, log in to one of your source cluster hosts. This is the same amount of records that you produced in the source topic with kafka-producer-perf-test.

Management 69

Management Testing Data Processing Big Data 69

Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. DataRobot Notebooks is a fully hosted and managed notebooks platform with auto-scaling compute capabilities so you can focus more on the data science and less on low-level infrastructure management.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

IBM Big Data Hub

JANUARY 16, 2024

Businesses are increasingly embracing data-intensive workloads, including high-performance computing, artificial intelligence (AI) and machine learning (ML). It’s a crucial metric for gauging the environmental impact of data center operations. This metric varies based on the energy source. grams of CO2e B.

IT 97

IT Cost-Benefit Consulting Measurement 97

DataRobot Blog

FEBRUARY 2, 2023

Large language models, also known as foundation models, have gained significant traction in the field of machine learning. Learn how you can easily deploy a pre-trained foundation model using the DataRobot MLOps capabilities, then put the model into production. What Are Large Language Models? pip install transformers==4.25.1

Modeling 52

Modeling Machine Learning Data Processing Interactive 52

CIO Business Intelligence

JUNE 8, 2022

The coming months are a leadership test for CIOs, and it’s a pass/fail grade.”. Demand transparency on everything — especially on metrics — and be transparent back. says the multinational food manufacturer hosts internal summits to show colleagues how advanced data and analytics can help drive growth. . Keep calm and lead on.

IT 133

IT Cost-Benefit Uncertainty Digital Transformation 133

AWS Big Data

JULY 26, 2023

The vector engine provides a simple, scalable, and high-performing similarity search capability in Amazon OpenSearch Serverless that makes it easy for you to build modern machine learning (ML) augmented search experiences and generative artificial intelligence (AI) applications without having to manage the underlying vector database infrastructure.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

Insight

MARCH 25, 2020

Live demo of the Pair web app Most recommender systems in use today leverage classical machine learning models. This design feature vector then queries the feature index libraries using L2 norm as the similarity search metrics ( cosine similarity is also available).

Deep Learning 53

Deep Learning Metrics Data Processing Interactive 53

DataRobot Blog

DECEMBER 20, 2022

We’ll then empirically test this assumption based on an example of real estate asset assessment. DataRobot combines these datasets and data types into one training dataset used to build machine learning models. parks and restaurants), and transportation networks.

Management 59

Management Machine Learning Optimization Modeling 59

The Unofficial Google Data Science Blog

JULY 18, 2023

Once we’ve answered that, we will then define and use metrics to understand the quality of human-labeled data, along with a measurement framework that we call Cross-replication Reliability or xRR. We will follow the example of Janson and Olsson , and start from this generalized definition of the metric, which they call iota.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

AWS Big Data

FEBRUARY 21, 2023

These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. Reliable computing infrastructure – The reliability of the computing infrastructure hosting Spark applications is the foundation of the whole Spark platform. Dave Thibault is a Sr.

Cost-Benefit 56

Cost-Benefit Informatics Optimization Management 56

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. AI Platform Single-Tenant SaaS are fully managed by DataRobot and replace disparate machine learning tools, simplifying management.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

AWS Big Data

JUNE 15, 2023

QuickSight is a unified BI service providing modern interactive dashboards, natural language querying, paginated reports, machine learning (ML) insights, and embedded analytics at scale. When I worked with the sales leaders, I learned their preferred terminology and business language through our usability sessions.

Sales 68

Sales Dashboards Visualization Testing 68

datapine

MAY 17, 2021

Without a doubt, the best way to drive maximum value from the metrics, insights, and information is through something called data discovery. Your Chance: Want to test a professional data discovery tool for free? Your Chance: Want to test a professional data discovery tool for free? We offer a 14 day free trial.

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161

O'Reilly on Data

JANUARY 25, 2021

We’re not pretending the frameworks themselves are comparable—Spring is primarily for backend and middleware development (though it includes a web framework); React and Angular are for frontend development; and scikit-learn and PyTorch are machine learning libraries. AI, Machine Learning, and Data.

Machine Learning 363

Machine Learning Software Testing Technology 363

Andrew White

JANUARY 11, 2021

On January 4th I had the pleasure of hosting a webinar. The work of data science is more tied to machine learning and so AI and those projects do not focus only on analysis but also automation. Storytelling is a nice one to use early on to test the approach. It is meant to be a desk-reference for that role for 2021.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

MAY 1, 2023

As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. When treating a patient, a doctor may wish to study the patient’s vital metrics in comparison to those of their peer group. They can also create custom calculations and metrics, and build new data visualizations.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52