Domino Data Lab

APRIL 3, 2019

Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. That presented an opportunity to learn, putting me in the same position as much of the audience. Enterprise Repository Era” (1990–2010) – first generation DG solutions.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. Data poisoning attacks.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

FineReport

APRIL 26, 2023

This is why big tech companies are switching to Spark as it is highly suitable for machine learning and artificial intelligence. MongoDB MongoDB, which gained popularity in 2010, is a NoSQL document-oriented database platform that is free and open-source. Real-time processing: Spark Streaming can handle real-time streaming.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

O'Reilly on Data

SEPTEMBER 19, 2023

They’d grown tired of learning what is; now they wanted to know what’s next. Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. It felt like, almost overnight, all of machine learning took on some kind of neural backend. Those algorithms packaged with scikit-learn?

Machine Learning 247

Machine Learning Testing Modeling Cost-Benefit 247

O'Reilly on Data

JULY 20, 2021

After the release of the iPad in 2010 Craig Hockenberry discussed the great value of communal computing but also the concerns : “When you pass it around, you’re giving everyone who touches it the opportunity to mess with your private life, whether intentionally or not. There is a tradeoff between the trust and risk. Source: [link].

Risk 304

Risk Software Interactive Modeling 304

Sisense

APRIL 14, 2020

Data is everywhere and every company is focused on what to do with their available data stores: customer journey follow-ups, harvesting precious behavioral insights, performing market analyses, and uncovering sales predictions through Machine Learning, just to name a few. Defining a social network. But this was an easy case.

Machine Learning 105

Machine Learning Measurement People Analytics Sales 105

Occam's Razor

AUGUST 28, 2017

Machine Learning is already changing lots of fields, the one I’m most excited about is what’s happening in healthcare. From the ability to speed up discovery of new medicines to the unbelievable speed with which Machine Learning techniques are becoming particularly adept at diagnosis (think blood reports, X-rays, cancers etc.).

Deep Learning 139

Deep Learning Machine Learning Marketing Strategy 139

The Unofficial Google Data Science Blog

AUGUST 27, 2019

A machine learning classifier serves this task perfectly. To demonstrate this issue, consider the following toy example of near-optimal importance sampling with categorical scores: Score Prevalence Population Proportion Sample Proportion Low Risk 0.1% High Risk 10% 5% 33.3% Statistical Science. 16 (2): 101–133. [3]

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Peter James Thomas

AUGUST 30, 2018

Limitations in the state of the art in machine learning. It is indeed true that Machine Learning can be quite good at dealing with some types or bad or missing data. A survey of Business Intelligence / Data Warehousing professionals back in 2010 would have generated something very like the list above.

Data Science 75

Data Science Data Quality Machine Learning Business Intelligence 75

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. Observability” risks becoming the new name for monitoring.

Machine Learning 363

Machine Learning Software Testing Technology 363