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

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.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

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. Artificial Intelligence (AI). Already in our shortlist of tech buzzwords 2019, artificial intelligence is on the front scene for next year again. Connected Retail.

Technology 279

Technology Internet of Things IT IoT 279

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

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. Rinse, lather, repeat. Those are table stakes in this game.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

JULY 2, 2019

See also: Caroline Lemieux’s slides for that NeurIPS talk, and Rohan Bavishi’s video from the RISE Summer Retreat 2019. The authors of AutoPandas observed that: The APIs for popular data science packages tend to have relatively steep learning curves. Program Synthesis 101 ” – Alexander Vidiborskiy (2019-01-20).

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CIO Business Intelligence

APRIL 15, 2022

Derek Driggs, a machine learning researcher at the University of Cambridge, together with his colleagues, published a paper in Nature Machine Intelligence that explored the use of deep learning models for diagnosing the virus. The paper determined the technique not fit for clinical use.

Analytics 145

Analytics Machine Learning Insurance Testing 145

Smart Data Collective

OCTOBER 14, 2019

Ludwig is a tool that allows people to build data-based deep learning models to make predictions. In September 2019, Google decided to make it’s Differential Privacy Library available as an open-source tool. Here are some open-source options to consider. You don’t even need coding knowledge to get started with it.

Data Science 69

Data Science Machine Learning Big Data Interactive 69

O'Reilly on Data

MAY 21, 2019

Here are some typical ways organizations begin using machine learning: Build upon existing analytics use cases: e.g., one can use existing data sources for business intelligence and analytics, and use them in an ML application. A typical data pipeline for machine learning. Use ML to unlock new data types—e.g.,

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238