Domino Data Lab

MARCH 16, 2021

We are at an interesting time in our industry when it comes to validating models – a crossroads of sorts when you think about it. There is an opportunity for practitioners and leaders to make a real difference by championing proper model validation. Explaining how deep neural networks work is hard to do. Saliency Maps.

Modeling 122

Modeling Deep Learning Testing Optimization 122

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. I will highlight the results of a recent survey on machine learning adoption, and along the way describe recent trends in data and machine learning (ML) within companies.

Machine Learning 234

Machine Learning Technology Deep Learning Data Science 234

IBM Big Data Hub

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? That’s where the foundation model enters the picture.

Modeling 56

Modeling Cost-Benefit Data Lake Machine Learning 56

O'Reilly on Data

FEBRUARY 4, 2019

As interest in machine learning (ML) and AI grow, organizations are realizing that model building is but one aspect they need to plan for. Machine Learning model lifecycle management. As noted above, ML and AI involves more than model building. Deep Learning. Text and Language processing and analysis.

Machine Learning 276

Machine Learning Enterprise IoT Big Data 276

Domino Data Lab

JANUARY 20, 2019

What if there was a way to quantitatively measure whether your machine learning (ML) model reflects specific domain expertise or potential bias? TCAV “uses directional derivatives to quantify the degree to which a user-defined concept is important to a classification result” ( Kim et al 2018 ). Introduction.

Testing 63

Testing Modeling Machine Learning Data Science 63

CIO Business Intelligence

SEPTEMBER 7, 2022

Dubbed Cropin Cloud, the suite comes with the ability to ingest and process data, run machine learning models for quick analysis and decision making, and several applications specific to the industry’s needs. Founded in 2016, Malaysian startup Agritix offers a plantation workforce management solution, dubbed Agritix Workforce.

B2B 80

B2B Contextual Data IoT Deep Learning 80

Domino Data Lab

JULY 17, 2021

The system here will identify, via some meaningful sense, which existing speakers’ model does the utterance match. If the unknown utterance is spoken by a speaker outside the list of existing speakers, the model will nonetheless map it to some speaker from that list. It determines whether the individual is who they claim to be.

Modeling 64

Modeling Testing Machine Learning Measurement 64

CIO Business Intelligence

APRIL 17, 2024

Similarly, clothing brand Under Armour recently produced an ad that used AI-generated 3D models of the British boxer Anthony Joshua, based on videos they took of him in the past. But discussions are underway within VTT about how to protect and commercialize the AI models they develop. “I

Enterprise 109

Enterprise Testing Digital Transformation Software 109

CIO Business Intelligence

DECEMBER 1, 2023

LexisNexis has been playing with BERT, a family of natural language processing (NLP) models, since Google introduced it in 2018, as well as Chat GPT since its inception. We’ll take the optimal model to answer the question that the customer asks.” But the foray isn’t entirely new. We will pick the optimal LLM.

Cost-Benefit 112

Cost-Benefit Digital Transformation Machine Learning Optimization 112

O'Reilly on Data

MARCH 7, 2019

Language understanding benefits from every part of the fast-improving ABC of software: AI (freely available deep learning libraries like PyText and language models like BERT ), big data (Hadoop, Spark, and Spark NLP ), and cloud (GPU's on demand and NLP-as-a-service from all the major cloud providers). Stanford Core NLP.

Deep Learning 224

Deep Learning Testing Machine Learning Modeling 224

CIO Business Intelligence

APRIL 25, 2023

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. Five years later, transformer architecture has evolved to create powerful models such as ChatGPT. Meanwhile, however, many other labs have been developing their own generative AI models.

Experimentation 100

Experimentation Enterprise Deep Learning Modeling 100

O'Reilly on Data

APRIL 19, 2021

Relatively few respondents are using version control for data and models. Tools for versioning data and models are still immature, but they’re critical for making AI results reproducible and reliable. The biggest skills gaps were ML modelers and data scientists (52%), understanding business use cases (49%), and data engineering (42%).

Enterprise 353

Enterprise Modeling Risk Manufacturing 353

Rocket-Powered Data Science

DECEMBER 16, 2018

In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters. There are also examples of cold start in supervised machine learning (where you do have class labels on the training data).

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

CIO Business Intelligence

MAY 30, 2024

Most recently, she has served as EVP and chief customer and technology officer at Ameren, which she joined 2018 as SVP and chief digital and information officer before adding customer experience and operations in 2023. It has been around since the 1950s with machine learning.

Data Quality 75

Data Quality Key Performance Indicator Digital Transformation Management 75

Corinium

JUNE 6, 2019

Beyond that, we recommend setting up the appropriate data management and engineering framework including infrastructure, harmonization, governance, toolset strategy, automation, and operating model. It is also important to have a strong test and learn culture to encourage rapid experimentation.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. Using ML models to search more effectively brought the search space down to 102—which can run on modest hardware. Program Synthesis Papers at ICLR 2018 ” – Illia Polosukhin (2018-05-01). Introduction.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Rocket-Powered Data Science

DECEMBER 15, 2018

Many unsupervised learning models can converge more readily and be more valuable if we know in advance which parameterizations are best to choose. If we cannot know that ( i.e., because it truly is unsupervised learning), then we would like to know at least that our final model is optimal (in some way) in explaining the data.

Machine Learning 171

Machine Learning Optimization Metrics Modeling 171

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. In 2018, Reuters broke the news that Amazon had scrapped the project.

Analytics 141

Analytics Machine Learning Insurance Testing 141

Cloudera

NOVEMBER 25, 2021

With the introduction of ML and Deep Learning (DL), it is now possible to build AI systems that have no ethical considerations at all. This often leads to clearer links between rules and unethical outcomes. . An unconstrained AI system will be optimised for whatever its output is.

Insurance 96

Insurance Machine Learning Deep Learning Reporting 96

CIO Business Intelligence

MAY 1, 2024

ChatGPT e le hallucination sui casi giudiziari I progressi compiuti nel 2023 dai large language models (LLM) hanno suscitato un interesse diffuso per il potenziale di trasformazione dell’IA generativa in quasi tutti i settori. Nel 2018, Reuters dà la notizia [in inglese] dell’abbandono del progetto da parte di Amazon [in inglese].

Software 87

Software Deep Learning Machine Learning Modeling 87

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. offers many statistics and machine learning abilities.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

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). The first survey started as a simple exploration into mainstream adoption of machine learning (ML). What’s been the impact of using ML models on culture and organization? Who builds their models?

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Data Science and Beyond

OCTOBER 15, 2017

Here are my thoughts from 2014 on defining data science as the intersection of software engineering and statistics , and a more recent post on defining data science in 2018. The hardest parts of data science are problem definition and solution measurement, not model fitting and data cleaning , because counting things is hard.

Data Science 71

Data Science Deep Learning Machine Learning Data-driven 71

Domino Data Lab

SEPTEMBER 9, 2019

We have configured the default Compute Environment in Domino to include all of the packages, libraries, models, and data you’ll need for this tutorial. That nlp variable is now your gateway to all things spaCy and loaded with the en_core_web_sm small model for English. deep learning on edge devices. Getting Started.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110

Insight

FEBRUARY 13, 2019

In late 2018, Google open-sourced BERT, a powerful deep learning algorithm for natural language processing. This allows BERT to provide significantly higher performance than models that are only able to leverage a small task-specific dataset. Download the BERT model files. Prior to Insight, he was at IBM Watson.

Testing 72

Testing Machine Learning Deep Learning Modeling 72

Domino Data Lab

FEBRUARY 10, 2019

I once ran a Kaggle competition where thousands of people competed around the world to model my data. 68% accuracy was clearly the limit on the data with the best most up-to-date machine learning techniques. Engineering projects generally move forward, but machine learning projects can completely stall. We might expect that.

Machine Learning 63

Machine Learning Modeling Deep Learning Metrics 63

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. This feature hierarchy and the filters that model significance in the data, make it possible for the layers to learn from experience.

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

APRIL 3, 2019

Plus it’s well-nigh time for “machine learning natives” to jump into the dialog about DG. So this month let’s explore these themes: 2018 represented a flashpoint for DG fails, prompting headlines worldwide and resulting in much-renewed interest in the field. More Policies Emerged” (2010-2018). There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Smart Data Collective

MAY 17, 2021

billion in 2018. All that performance data can be fed into a machine learning tool specifically designed to identify certain events, failures or obstacles. Predictive models, estimates and identified trends can all be sent to the project management team to speed up their decisions. Organizations have already realized this.

Big Data 100

Big Data Cost-Benefit IoT Machine Learning 100

O'Reilly on Data

SEPTEMBER 11, 2019

So, we used a form of the Term Frequency-Inverse Document Frequency (TF/IDF) technique to identify and rank the top terms in this year’s Strata NY proposal topics—as well as those for 2018, 2017, and 2016. 2 in frequency in proposal topics; a related term, “models,” is No. An ML-related topic, “models,” was No. 221) to 2019 (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Insight

MARCH 5, 2019

As machine learning (ML) algorithms increase in popularity and the “black boxes” of neural networks in deep learning (DL) become the industry standard, pulling out the demographic information and the user history responsible for each undesired rec becomes next to impossible to achieve.

Machine Learning 71

Machine Learning Internet of Things Recreation/Entertainment IoT 71

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. The year 2018 was what Wall Street Journal called “ a global reckoning on data governance.”

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Cloudera

SEPTEMBER 12, 2018

. — Mike Barlow, author of “Learning to Love Data Science” (O’Reilly Media). And now, without further delay, we are excited to announce the winners of the 2018 Data Impact Awards, listed by award theme and category: Business Impact. Two weeks ago, we announced the finalists. Cloud Success: .

Machine Learning 45

Machine Learning Big Data Data Science Data Warehouse 45

Insight

JANUARY 14, 2020

Lauren Holzbauer was an Insight Fellow in Summer 2018. a “pre-trained” model) to be recycled and reused for many different tasks. Keras is an open source deep learning API that was written in Python and runs on top of Tensorflow, so it’s a little more user-friendly and high-level than Tensorflow.

Metrics 58

Metrics Optimization Modeling Testing 58

Insight

DECEMBER 30, 2019

Lauren Holzbauer was an Insight Fellow in Summer 2018. As we will see, this fundamental shift in methodology led to a new generation of computer vision models with unprecedented ability. Next, we will explain how each layer works, why they are ordered this way, and how everything comes together to form such a powerful model.

Visualization 72

Visualization Modeling Machine Learning IT 72

Insight

MARCH 28, 2019

For the Fall 2018 session of the Insight Fellows Program in NYC, we launched a new partnership with Thinknum , a company that provides alternative data indexed from the web to institutional investors and corporations? Utilize information hidden away in online employee reviews. about 4,000 in all.

Dashboards 70

Dashboards Visualization Data Science Machine Learning 70