O'Reilly on Data

JULY 28, 2020

This tradeoff between impact and development difficulty is particularly relevant for products based on deep learning: breakthroughs often lead to unique, defensible, and highly lucrative products, but investing in products with a high chance of failure is an obvious risk. arbitrary stemming, stop word removal.).

Marketing 362

Marketing Experimentation Metrics Testing 362

O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 332

Management Machine Learning Experimentation Metrics 332

IBM Big Data Hub

FEBRUARY 14, 2024

Deliver new insights Expert systems can be trained on a corpus—metadata used to train a machine learning model—to emulate the human decision-making process and apply this expertise to solve complex problems. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

Cost-Benefit 87

Cost-Benefit Insurance Unstructured Data Machine Learning 87

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. In short, the virtuous cycle is growing.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

O'Reilly on Data

MARCH 18, 2020

Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI. Supervised learning is dominant, deep learning continues to rise. AI tools organizations are using.

Enterprise 309

Enterprise Deep Learning Data Governance Risk 309

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. One of the longer-term trends that we’re seeing with Airflow , and so on, is to externalize graph-based metadata and leverage it beyond the lifecycle of a single SQL query, making our workflows smarter and more robust. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Ontotext

MAY 22, 2023

We use other deep learning techniques for such tasks. Atanas Kiryakov : A CMS typically contains modest metadata , describing the content: date, author, few keywords and one category from a taxonomy. Knowledge graphs are all about using semantic metadata to serve these purposes. That’s something that LLMs cannot do.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Domino Data Lab

OCTOBER 9, 2019

Metadata Challenges. NOAA teams face substantial challenges in terms of metadata exchange: much of their incoming raw sensor telemetry is time-series data, which uses a netCDF TF format natively. The metadata must be converted into both W3C and ISO standards for publication. How cool is that?!

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. Parquet also stores type metadata which makes reading back and processing the files later slightly easier. Introduction. The raw data is in a series of CSV files.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

O'Reilly on Data

JUNE 19, 2019

Metadata and artifacts needed for a full audit trail. Related content : “Modern Deep Learning: Tools and Techniques” - a new tutorial at the Artificial Intelligence conference in San Jose. Becoming a machine learning company means investing in foundational technologies”.

Modeling 193

Modeling Machine Learning Testing Metrics 193

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. 1] Users can access data through a single point of entry, with a shared metadata layer across clouds and on-premises environments.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

CIO Business Intelligence

MARCH 9, 2022

If those in charge of managing the data lake don’t create precise processes and metadata for organizing data, the lake can quickly devolve into what’s come to be known as a “data swamp”—a data lake that makes it hard for users to locate data. . On the other hand, they don’t support transactions or enforce data quality.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

DataRobot Blog

MARCH 9, 2022

With that said, recent advances in deep learning methods have allowed models to improve to a point that is quickly approaching human precision on this difficult task. LSTMs and other recurrent neural networks RNNs are probably the most commonly used deep learning models for NLP and with good reason. More advanced models.

Machine Learning 52

Machine Learning Deep Learning Modeling Measurement 52

O'Reilly on Data

MARCH 20, 2019

Watermarking is a term borrowed from the deep learning security literature that often refers to putting special pixels into an image to trigger a desired outcome from your model. A lot of the contemporary academic machine learning security literature focuses on adaptive learning, deep learning, and encryption.

Modeling 221

Modeling Machine Learning Predictive Modeling Consulting 221

Domino Data Lab

JUNE 26, 2019

On the flip side, when data scientists mark a project as complete with a description of the project conclusion, Domino also captures this metadata for project tracking and future references. All of this metadata captured can be useful for organizational learning, organize projects and help to avoid similar issues in the future. .

Data Science 65

Data Science Dashboards Metadata Snapshot 65

Domino Data Lab

JULY 22, 2019

and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries. They’d like to do something more efficient when they’re training a lot of deep learning models. Now, we have low-power devices and inference running on them.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Ontotext

FEBRUARY 26, 2024

Quality assurance process, covering gold standard creation , extraction quality monitoring, measurement, and reporting via Ontotext Metadata Studio. Leveraging LLMs for information extraction tasks, such as named entities recognition, entity linking , and event and relationship extraction.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

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

Smart Data Collective

OCTOBER 13, 2021

Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields). As we have already said, the challenge for companies is to extract value from data, and to do so it is necessary to have the best visualization tools.

Visualization 132

Visualization Cost-Benefit Big Data Prescriptive Analytics 132

Domino Data Lab

SEPTEMBER 9, 2019

metadata=convention_df["speaker"]? ). 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. deep learning on edge devices. category="democrat",?. width_in_pixels=1000,?.

Deep Learning 110

Deep Learning Machine Learning Visualization Data Science 110