Smart Data Collective

FEBRUARY 14, 2023

The best part is that many of these web apps are using AI technology to provide the optimal user experience. Web developers know that they’re working within the constraints of a browser, so they tend to optimize their product to operate as efficiently as possible with fewer computing resources.

Risk 115

Risk Technology Optimization Machine Learning 115

Smart Data Collective

JULY 4, 2022

Donald Taylor conducted the L&D Global Sentiment Survey in 2017. It uses powerful analytics, confidence-based evaluations, and pre-learning tests to assist businesses in avoiding the pitfalls of generic learning. Organizations, on the other hand, can actively utilize resources to achieve optimal training ROI.

Data-driven 127

Data-driven Big Data Interactive Recreation/Entertainment 127

IBM Big Data Hub

JULY 19, 2023

The exponential leap in generative AI is already transforming many industries: optimizing workflows , helping human teams focus on value added tasks and accelerating time to market. Code creation: Code co-pilot, code conversion, create technical documentation, test cases and more. Why IBM Consulting for generative AI on AWS?

Consulting 62

Consulting Machine Learning Manufacturing Optimization 62

IBM Big Data Hub

MAY 26, 2023

Cloud computing offers the potential to redefine and personalize customer relationships, transform and optimize operations, improve governance and transparency, and expand business agility and capability. In 2017, 94% of hospitals used electronic clinical data from their EHR.

Consulting 77

Consulting Cost-Benefit Optimization Machine Learning 77

The Unofficial Google Data Science Blog

APRIL 23, 2024

If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). However, joint optimization is possible by increasing both $x_1$ and $x_2$ at the same time.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Sisense

JULY 10, 2019

As of 2017, Linux was running 90% of the public cloud workload. Given this importance, we made it an organizational priority to invest in a Sisense on Linux deployment in late 2017. When I was tasked with the responsibility of building a Sisense Linux deployment in late 2017, a few small steps had already been taken.

IT 69

IT Testing Technology Sales 69

Ontotext

SEPTEMBER 24, 2020

Or this – a digital twin of an entire city being used by the public and private sector as a three-dimensional model that can be analyzed, controlled and tested in real time. And this is where the value-proposition of a digital twin technology, listed among the top 10 strategic technologies since 2017, comes into play.

IT 59

IT Digital Transformation Manufacturing Modeling 59

CIO Business Intelligence

APRIL 24, 2023

How we got here The most notable enabling technologies in generative AI are deep learning, embeddings, transfer learning (all of which emerged in the early to mid-2000s), and neural net transformers (invented in 2017). One of the most important of such architectures, the “transformer,” was developed in 2017.

Enterprise 52

Enterprise Deep Learning Modeling Machine Learning 52

Jet Global

SEPTEMBER 4, 2020

When Microsoft released the next generation of the product in 2017, Microsoft Dynamics 365 for Finance and Supply Chain Management (D365F&SCM) , there were some significant changes behind the scenes. As of this writing, that product is still in testing, and no formal release date has been announced. Data Entities.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Insight

JUNE 2, 2019

To provide a consistent installation, all instructions are written after testing on Ubuntu 18.04 bin/scala to provide /usr/bin/scala (scala) in auto mode $ scala -version Scala code runner version 2.11.12 -- Copyright 2002-2017, LAMP/EPFL Please make note of the Scala version here. on AWS using EC2 Instances. Setting up scala (2.11.12-4~18.04).

Testing 67

Testing Management Data Processing Interactive 67

Hurwitz & Associates

SEPTEMBER 21, 2018

New projects announced at VMworld included Project Dimension and Project Magna, Both projects were demonstrated at VMworld as working beta programs, but they are in the final stages of testing before going into production. Project Magna is a VMware technology preview that leverages AI/ML to self-optimize virtual infrastructure.

Software 40

Software IT Strategy IoT 40

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. A catalog or a database that lists models, including when they were tested, trained, and deployed.

Modeling 194

Modeling Machine Learning Testing Metrics 194

Domino Data Lab

MARCH 16, 2021

Lately, however, there is very exciting research emerging around building concepts from first principles with the goal of optimizing the higher layers to be human-readable. Instead of optimizing for pure accuracy, the network is constructed in a way that focuses on strong definitions of high-level concepts. Image source: [link].

Modeling 122

Modeling Deep Learning Testing Optimization 122

O'Reilly on Data

MARCH 23, 2023

Many of these go slightly (but not very far) beyond your initial expectations: you can ask it to generate a list of terms for search engine optimization, you can ask it to generate a reading list on topics that you’re interested in. It was not optimized to provide correct responses. It has helped to write a book.

IT 262

IT Modeling Testing Risk 262

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ Agile was originally about iterating fast on a code base and its unit tests, then getting results in front of stakeholders. Challenges for Transparency ”. A Survey Of Methods For Explaining Black Box Models ”.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JULY 2, 2019

SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. Here’s a sampler of related papers and articles if you’d like to dig in further: “ Synthesizing Programs with Deep Learning ” – Nishant Sinha (2017-03-25). “

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CIO Business Intelligence

JUNE 6, 2022

While bad CX costs businesses thousands of customers and billions of dollars every year, companies that optimize CX increase customer satisfaction, reduce customer churn, improve employee satisfaction, and boost revenues. As Warren Buffet stated: “It takes 20 years to build a reputation and five minutes to ruin it.”.

Digital Transformation 105

Digital Transformation Interactive Testing Optimization 105

CIO Business Intelligence

MARCH 22, 2022

He brings expertise in developing IT strategy, digital transformation, AI engineering, process optimization and operations. In 2017 he left to become a senior vice president at Reliance Payment Services. December 2021. Airtel CISO Manish Tiwari joins Fractal as CIO. Fractal Analytics has appointed Manish Tiwari as its CIO.

Internet Publishing and Broadcasting 98

Internet Publishing and Broadcasting Digital Transformation Insurance Recreation/Entertainment 98

The Unofficial Google Data Science Blog

JULY 22, 2020

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

Experimentation 95

Experimentation Statistics Testing Strategy 95

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

For example, consider the following simple example fitting a two-dimensional function to predict if someone will pass the bar exam based just on their GPA (grades) and LSAT (a standardized test) using the public dataset (Wightman, 1998). Curiosities and anomalies in your training and testing data become genuine and sustained loss patterns.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

O'Reilly on Data

JULY 25, 2023

To provide some coherence to the music, I decided to use Taylor Swift songs since her discography covers the time span of most papers that I typically read: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022. This choice also inspired me to call my project Swift Papers.

Consulting 246

Consulting Interactive Software IT 246

Insight

MARCH 25, 2019

Bugs in a third-party CDN provider’s system, such as this one from 2017, can have serious implications for the security and privacy of your users. Apart from the ease of scaling, kubeCDN can also optimize infrastructure costs by tearing down regions during periods of low user activity.

Data Processing 106

Data Processing Cost-Benefit Optimization Metrics 106

Smarten

SEPTEMBER 6, 2019

With true self-serve business intelligence and analytics solutions, the average business user can perform data preparation, test theories and hypotheses by prototyping on their own and share clear, objective data with others.

Analytics 51

Analytics IT Business Intelligence Testing 51

Cloudera

MAY 18, 2021

It helps identify risk exposures, informs pre-trade decisions, and is reported to regulators for stress testing. 2] Bayraktar, Erhan and Munk, Alexander, Mini-Flash Crashes, Model Risk, and Optimal Execution (May 27, 2017). Intraday VaR. Value-at-Risk (VaR) is a widely used metric in risk management. Citations. [1]

Risk 93

Risk Marketing Risk Management Data-driven 93

Occam's Razor

SEPTEMBER 15, 2014

Company UX leaders are happy to stink less by taking the sub-optimal path of responsive design, rather than create a mobile-unique experience (your customers tend to do different things on your desktop site than your mobile site!). Many reasons. CEOs still don't get it. The next tab is more fun/important, the search performance report.

Metrics 141

Metrics Reporting Analytics Marketing 141

Domino Data Lab

AUGUST 1, 2021

After forming the X and y variables, we split the data into training and test sets. Next, we pick a sample that we want to get an explanation for, say the first sample from our test dataset (sample id 0). For sample 23 from the test set, the model is leaning towards a bad credit prediction. show_in_notebook(). References.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Occam's Razor

DECEMBER 8, 2017

The lesson is about the limitation of optimizing for a local maxima, usually in a silo. I believe this approach optimizes for a local maxima (the media buying bubble) and does not create the necessary incentives to solve for the global maxima (short or long-term business success). I believe this is necessary, but not sufficient.

Broadcasting 121

Broadcasting Measurement Marketing Sales 121

datapine

NOVEMBER 27, 2019

Another increasing factor in the future of business intelligence is testing AI in a duel. Prescriptive analytics can help you optimize scheduling, production, inventory, and supply chain design to deliver what your customers want in the most optimized way. 5) Collaborative Business Intelligence. BN by 2023, with a CAGR of 13.6%

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

DataRobot Blog

OCTOBER 3, 2017

Finally, Clarity Insights created a joint solution on AWS CloudFormation templates allowing a point-and-click way to stand up a fully-functional data lake using Cloudera , Paxata , and Zoomdata optimized on Intel processors. The post 3 Major Trends at Strata New York 2017 appeared first on DataRobot AI Cloud. Try now for free.

Data Lake 52

Data Lake Data Architecture Advertising Insurance 52

O'Reilly on Data

DECEMBER 19, 2018

We won’t be writing code to optimize scheduling in a manufacturing plant; we’ll be training ML algorithms to find optimum performance based on historical data. have a large body of tools to choose from: IDEs, CI/CD tools, automated testing tools, and so on. If humans are no longer needed to write enterprise applications, what do we do?

Machine Learning 261

Machine Learning Software Metadata Testing 261

CIO Business Intelligence

APRIL 12, 2022

Perforce already owns development tools such as Helix and the testing tools, including Perfecto and BlazeMeter. It will add it to its Spot by NetApp portfolio, the collection of SaaS tools built around the cloud management and cost optimization company it bought in 2022. Microsoft buys Minit to optimize process automation.

Technology 143

Technology Enterprise Consulting Software 143

O'Reilly on Data

JANUARY 25, 2021

Both SRE and DevOps emphasize similar practices: version control (62% growth for GitHub, and 48% for Git), testing (high usage, though no year-over-year growth), continuous deployment (down 20%), monitoring (up 9%), and observability (up 128%). It’s particularly difficult if testing includes issues like fairness and bias.

Machine Learning 363

Machine Learning Software Testing Technology 363

Alation

AUGUST 26, 2021

HBR Review May/June 2017. It relies on data intelligence software to be managed and optimized. Next, you test these use cases with the software chosen. Field Test Use Cases. Once you’ve defined your goals and use cases , it’s time to put them to the test. Source: “What’s Your Data Strategy?” Profiling tools.

Metadata 64

Metadata Data Governance Dashboards Software 64

Occam's Razor

OCTOBER 12, 2017

When you go to the interview, the hiring company will proceed to ask questions that test your competency in the listed job requirements. Test for analytics experience AND explore the level of analytical thinking the job candidate possesses. Optimal Starting SCOTUS Starting Points. This is not the future, it is Nov 2017.

Marketing 136

Marketing Analytics Machine Learning Strategy 136