Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

DataKitchen

JUNE 24, 2021

Chapin shared that even though GE had embraced agile practices since 2013, the company still struggled with massive amounts of legacy systems. Most companies have legacy models in software development that are well-oiled machines. Success Requires Focus on Business Outcomes, Benchmarking.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

CIO Business Intelligence

FEBRUARY 10, 2023

But for two years, we were testing limits within the public cloud.” Randich, who came to FINRA.org in 2013 after stints as co-CIO of Citigroup and former CIO of Nasdaq, is no stranger to the public cloud. “We spent about a year and a half going through several bottlenecks, taking them out one at a time with Amazon engineers.

Unstructured Data 105

Unstructured Data Data Lake Machine Learning Enterprise 105

Edwin Chen

AUGUST 14, 2014

How can we understand causal lifts in the absence of an A/B test? This is where propensity modeling, or other techniques of causal inference, comes into play. Propensity Modeling. So suppose we want to model the effect of drinking Soylent using a propensity model technique. a negative effect).

Modeling 75

Modeling Measurement Sales Testing 75

CIO Business Intelligence

MAY 4, 2022

In fact, it has been available since 2013. After adopting the MITRE ATT&CK as their common language and model for describing attacks and attackers, the critical infrastructure organization’s security team can now translate between operational aspects of security and the potential impact of a successful attack.

Measurement 105

Measurement Visualization Marketing Testing 105

AWS Big Data

JULY 11, 2024

In this blog post, we propose a solution based on Amazon OpenSearch Service for similarity search and the pretrained model ProtT5-XL-UniRef50 , which we will use to generate embeddings. ProtT5-XL-UniRef50 is based on the t5-3b model and was pretrained on a large corpus of protein sequences in a self-supervised fashion.

Machine Learning 97

Machine Learning Modeling Data Processing Testing 97

CIO Business Intelligence

APRIL 4, 2024

The good news is that you can ask any of the large language models (LLMs) like ChatGPT to rewrite paragraphs or sections for improved comprehension or make it more concise. Delete old data I lived in Hong Kong 2008-2013 and one of my most pleasurable weekends was a trip to see an incredible band at the MGM hotel in Macau.

Cost-Benefit 98

Cost-Benefit Data Governance Testing Modeling 98

Domino Data Lab

DECEMBER 1, 2019

This article covers how to detect data drift for models that ingest image data as their input in order to prevent their silent degradation in production. Introduction: preventing silent model degradation in production. This article explores an approach that can be used to detect data drift for models that classify/score image data.

Machine Learning 77

Machine Learning Modeling Deep Learning Testing 77

Sisense

APRIL 2, 2019

This is when IT operations and software development communities started to talk about problems in the software industry, specifically around the traditional software development model. While developers enjoy these streamlined processes, other team members may need more help in coordinating sequences for deploying and testing the application.

Software 80

Software Testing Enterprise IT 80

AWS Big Data

NOVEMBER 14, 2023

Amazon Redshift data sharing enables you to evolve your Amazon Redshift deployment architectures into a hub-and-spoke or data mesh model to better meet performance SLAs, provide workload isolation, perform cross-group analytics, and onboard new use cases, all without the complexity of data movement and data copies.

Data Warehouse 64

Data Warehouse Analytics Testing Cost-Benefit 64

CIO Business Intelligence

MAY 18, 2023

By defining team types, their fundamental interactions, and the science behind them, you learn how to better model your organizations according to these definitions. We need to really understand the drivers that influence customer and employee trust, as this is increasingly a litmus test,” says Johnson.

IT 130

IT Recreation/Entertainment Software Technology 130

AWS Big Data

FEBRUARY 1, 2024

Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. This is where model fine-tuning can help. Before you can fine-tune a model, you need to find a task-specific dataset. Next, we use Amazon SageMaker JumpStart to fine-tune the Llama 2 model with the preprocessed dataset.

Metadata 111

Metadata Modeling Data Processing Unstructured Data 111

bridgei2i

JULY 28, 2020

It is my immense pleasure to introduce you all to our guest today Ria Persad, she’s named as international woman of the year by Renewable Energy World in power engineering in 2013 and the lifetime achievement leader by Platts Global Energy awards in 2014. We need people who can test.

Enterprise 98

Enterprise Digital Transformation Insurance B2B 98

Insight

MAY 20, 2020

The tradeoff is that you’d have to follow Spark’s programming model and you wouldn’t have the same amount of control as if you built the infrastructure yourself. Here are detailed instructions on how to install and test an installation of Hadoop on AWS. It’s a small amount of control to give up for what you gain?—?but

Data Warehouse 106

Data Warehouse Optimization Interactive Cost-Benefit 106

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 113

Data Warehouse Analytics Data Lake Machine Learning 113

Domino Data Lab

APRIL 21, 2021

We’ll use a gradient boosting technique via XGBoost to create a model and I’ll walk you through steps you can take to avoid overfitting and build a model that is fit for purpose and ready for production. This is to prevent any information leakage into our test set. 2f%% of the test set."

Statistics 69

Statistics Machine Learning Modeling Metrics 69

AWS Big Data

MARCH 13, 2024

For building any generative AI application, enriching the large language models (LLMs) with new data is imperative. Ray cluster for ingestion and creating vector embeddings In our testing, we found that the GPUs make the biggest impact to performance when creating the embeddings. This breaks out to approximately 200 per record.

Data Processing 123

Data Processing Dashboards Machine Learning Metrics 123

IBM Big Data Hub

OCTOBER 16, 2023

Containers have increased in popularity and adoption ever since the release of Docker in 2013, an open-source platform for building, deploying and managing containerized applications. Containerization helps DevOps teams avoid the complications that arise when moving software from testing to production.

Dashboards 71

Dashboards Data Processing Metrics Software 71

Howard Dresner

AUGUST 27, 2013

Before the perfect storm, our tweetchat tribe (comprised of customers, vendors and consultants/analysts) were of the opinion that the growing “app” mentality for “cool stuff” among consumers and the easy-to-consume info in mobile apps could end up increasing trust and thus lead to less testing and faster releases.

Business Intelligence 60

Business Intelligence Finance Risk Data-driven 60

Smart Data Collective

MARCH 22, 2019

By 2020, the robotics technology market is expected to reach almost $83 bn, according to the Global Robotics Technology Market 2013-2020. The RaaS model has recently become a common occurrence in the agro sector. Test the suggestions in a single department and scale the implemented technologies factory-wide, if successful.

Manufacturing 61

Manufacturing Cost-Benefit Enterprise Technology 61

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

But most common machine learning methods don’t give posteriors, and many don’t have explicit probability models. More precisely, our model is that $theta$ is drawn from a prior that depends on $t$, then $y$ comes from some known parametric family $f_theta$. Here, our items are query-ad pairs. Calculate posterior quantities of interest.

KDD 40

KDD Testing Machine Learning Measurement 40

BizAcuity

DECEMBER 31, 2019

With the limited time F1 drivers have to test these days, rookies have to learn things very quickly – and he has done it very well. Killingsworth had 10 rebounds but they were outrebounded 48 – and none was more significant than the one on Brown’s missed free throw in the final seconds. I grew up on St.

Reporting 52

Reporting Testing Modeling IT 52

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

BizAcuity

MAY 10, 2022

Amazon strategically went with the pricing model of ‘on-demand’, allowing developers to pay only as-per their computational needs. 2013: Google launches Google Compute Engine (IaaS), its own version of EC2. AWS rolls out SageMaker, designed to build, train, test and deploy machine learning (ML) models.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Domino Data Lab

MARCH 27, 2019

This allows you to easily rearrange the steps (simply by moving lines), as well as to “comment out” particular steps to test and debug your analysis as you go. Kennedy, and La Guardia airports) in 2013. Analyzing Data Frames by Group. You’ll use a data set of flights that departed from New York City airports (including Newark, John F.

Statistics 85

Statistics Data Science Visualization IT 85

Occam's Razor

DECEMBER 9, 2013

One that reflects the customer expectations of 2013. Or Ford (it is amazing that in 2013, for such an expensive product, it looks so… 2005). Go buy a simple A/B testing tool ( Visual Website Optimizer , Optimizely ), go crazy optimizing every little thing to take money from the people who want to give it to you!

Marketing 165

Marketing Analytics Key Performance Indicator Optimization 165

CIO Business Intelligence

AUGUST 16, 2024

We need to really understand the drivers that influence customer and employee trust, as this is increasingly a litmus test,” says Johnson. By defining team types, their fundamental interactions, and the science behind them, you learn how to better model your organizations according to these definitions.

IT 137

IT Technology Management Software 137

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Jen Stirrup

FEBRUARY 1, 2023

The effects of AI will be magnified in the coming decade as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning.

Recreation/Entertainment 64

Recreation/Entertainment Testing Advertising Insurance 64

Occam's Razor

JANUARY 28, 2013

It shows the normal distribution of XS, S, L etc, but it also shows, how cool is this, the Model's size (S in this case), her height, bust, waist and hip size! You can't try the dress on, but this data helps you understand if it will look on you just like it does on the model. The model you see above just starts moving!

Marketing 165

Marketing Insurance Visualization IT 165

IBM Big Data Hub

FEBRUARY 22, 2024

Earning trust in the outputs of AI models is a sociotechnical challenge that requires a sociotechnical solution. There must be a concerted effort to make these principles a reality through consideration of the functional and non-functional requirements in the models and the governance systems around those models.

Metadata 91

Metadata Measurement Risk Modeling 91

Occam's Razor

APRIL 29, 2013

A benchmark for you: In 2013 if 30% of your time, Ms./Mr. If the simple A/B (test/control) experiment demonstrates that delivering display banner ad impressions to the test group delivers increased revenue, buy impressions to your heart's content. In the latter group I discovered that there were two common themes.

Marketing 166

Marketing Metrics Advertising Measurement 166

Insight

MARCH 12, 2020

In 2013, Robert Galbraith?—?an The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. More relevant to the AIgent is Google’s BERT model, a task-agnostic (i.e. an aspiring author?—?finished

Modeling 59

Modeling Metadata Publishing Sales 59

Jet Global

MAY 1, 2023

Companies like Tableau (which raised over $250 million when it had its IPO in 2013) demonstrated an unmet need in the market. These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Their dashboards were visually stunning.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

CIO Business Intelligence

MARCH 26, 2025

The combination of AI and search enables new levels of enterprise intelligence, with technologies such as natural language processing (NLP), machine learning (ML)-based relevancy, vector/semantic search, and large language models (LLMs) helping organizations finally unlock the value of unanalyzed data.

Knowledge Discovery 84

Knowledge Discovery Cost-Benefit Enterprise Modeling 84

AWS Big Data

NOVEMBER 27, 2024

Its low-cost storage model makes it economically feasible to store vast amounts of historical data for extended periods of time. In this post, we walk through the following steps to set up and test this integration: Create an S3 bucket. He has been focusing in the big data analytics space since 2013. Amazon EMR 7.2.0

Big Data 104

Big Data Data Processing Cost-Benefit Optimization 104