CIO Business Intelligence

APRIL 11, 2022

The amount of money lost to card-not-present fraud in 2020 was six times greater than what merchants lost in 2019, according to the Nilson Report. That wasn’t a fluke either, as the 2019 numbers were four times higher than 2018. Scaling Transaction Processing to Fight Fraud. Just starting out with analytics?

Deep Learning 59

Deep Learning Strategy Risk Data Quality 59

KDnuggets

OCTOBER 18, 2019

In this second part we want to outline our own experience building an AI application and reflect on why we chose not to utilise deep learning as the core technology used.

Deep Learning 55

Deep Learning Technology Optimization Machine Learning 55

FineReport

DECEMBER 19, 2019

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. Of course, other BI tools such as Power BI and Qlikview also have their own advantages. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

O'Reilly on Data

FEBRUARY 18, 2020

Growth is still strong for such a large topic, but usage slowed in 2018 (+13%) and cooled significantly in 2019, growing by just 7%. But sustained interest in cloud migrations—usage was up almost 10% in 2019, on top of 30% in 2018—gets at another important emerging trend. Still cloud-y, but with a possibility of migration.

Data-driven 335

Data-driven Software Statistics Marketing 335

Cloudera

NOVEMBER 15, 2021

Deep Learning, a subset of AI algorithms, typically requires large amounts of human annotated data to be useful. In 2019 OpenAI reported that the computational power used in the largest AI trainings has been doubling every 3.4 Here we briefly describe some of the challenges that data poses to AI. Data annotation.

Unstructured Data 86

Unstructured Data Recreation/Entertainment Structured Data Reporting 86

O'Reilly on Data

MARCH 31, 2020

At measurement-obsessed companies, every part of their product experience is quantified and adjusted to optimize user experience. They have deployed machine learning at scale to recommend movies and friends, personalize ads, and deliver search results. Managing Machine Learning Projects” (AWS). People + AI Guidebook” (Google).

Management 332

Management Machine Learning Experimentation Metrics 332

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

The first is that they are straightforward to optimize using traditional gradient-based optimizers as long as we pre-specify the placement of the knots. There is a robust set of tools for working with these kinds of constrained optimization problems. Other deep learning models can also be written in this form.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

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. See also: Caroline Lemieux’s slides for that NeurIPS talk, and Rohan Bavishi’s video from the RISE Summer Retreat 2019. Software writes Software?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

datapine

NOVEMBER 19, 2019

While we’ve seen traces of this in 2019, it’s in 2020 that computer vision will make a significant mark in both the consumer and business world. Already in our shortlist of tech buzzwords 2019, artificial intelligence is on the front scene for next year again. Artificial Intelligence (AI). Connected Retail. Hyperautomation.

Technology 279

Technology Internet of Things IT IoT 279

DataKitchen

APRIL 13, 2021

Observe, optimize, and scale enterprise data pipelines. . ParallelM — Moves machine learning into production, automates orchestration, and manages the ML pipeline. Acquired by DataRobot June 2019). DataMo – Datmo tools help you seamlessly deploy and manage models in a scalable, reliable, and cost-optimized way.

Testing 300

Testing Machine Learning Consulting Data Quality 300

O'Reilly on Data

SEPTEMBER 11, 2019

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. Deep learning,” for example, fell year over year to No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

KDnuggets

OCTOBER 11, 2019

You have heard the expression “there is no such thing as a free lunch” – well in machine learning the same principle holds. In fact there is even a theorem with the same name.

Machine Learning 88

Machine Learning Optimization Deep Learning 88

Domino Data Lab

MARCH 3, 2019

O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019). AI Adoption in the Enterprise: How Companies Are Planning and Prioritizing AI Projects in Practice (Feb 2019).

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

BizAcuity

MARCH 31, 2022

of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Marketers also have access to several AI softwares to save time and optimize their work at every step of the funnel. Integrating IoT and route optimization are two other important places that use AI.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Domino Data Lab

MAY 8, 2019

For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters. Perhaps if machine learning were solely being used to optimize advertising or ecommerce, then Agile-ish notions could serve well enough.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

MAY 21, 2019

Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. Machine learning is not only appearing in more products and systems, but as we noted in a previous post , ML will also change how applications themselves get built in the future.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

Business Over Broadway

DECEMBER 20, 2018

Predictive analytics and artificial intelligence capabilities provide a way to extract insights from that data to help you improve the customer experience and optimize customer loyalty. Looking ahead to 2018, data professionals are most interested in learning deep learning (41%).

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

O'Reilly on Data

JANUARY 25, 2021

Year-over-year (YOY) growth compares January through September 2020 with the same months of 2019. Let’s look at the data, starting at the highest level: O’Reilly online learning itself. O’Reilly Online Learning. Usage of O’Reilly online learning grew steadily in 2020, with 24% growth since 2019.

Machine Learning 363

Machine Learning Software Testing Technology 363

Domino Data Lab

SEPTEMBER 9, 2019

It’s important to note that machine learning for natural language got a big boost during the mid-2000’s as Google began to win international language translation competitions. The use cases for natural language have shifted dramatically over the past two years, after deep learning techniques arose to the fore.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110