CIO Business Intelligence

MAY 17, 2022

This particular hospital’s data science team had built a system to identify such comorbidities. If a correlation uncovered by the algorithm is weak, doctors might be subjecting patients to unnecessary tests that would be a waste of time and money for the hospital. Can we use nurse practitioners instead? Can we automate?”.

Risk 145

Risk Consulting Machine Learning Data Science 145

O'Reilly on Data

MARCH 7, 2019

If you don’t believe me, feel free to test it yourself with the six popular NLP cloud services and libraries listed below. In a test done during December 2018, of the six engines, the only medical term (which only two of them recognized) was Tylenol as a product. IBM Watson NLU. Azure Text Analytics. Amazon Comprehend (offline).

Deep Learning 232

Deep Learning Testing Machine Learning Modeling 232

Smart Data Collective

MARCH 23, 2022

Evan Morris of Towards Data Science discussed this in one of his recent articles. Morris points out that AI helps with automated testing. Companies can use AI technology to test hidden elements of their websites and can see how they perform under various browsers. between Q1 of 2017 and Q1 of 2018.

Cost-Benefit 100

Cost-Benefit Data mining Sales Testing 100

Smarten

MAY 18, 2022

Who sold the most fruit juice in Phonix, Arizona in Christmas of 2018? Who sold the most fruit juice in Phoenix Az in Christmas of 2018? With context-driven searching, the sales manager can ask all kinds of questions to test theories and hypotheses. Sample Phonetics-Based Question. Sample Abbreviation Question.

Data-driven 67

Data-driven Sales Metrics Testing 67

Domino Data Lab

JULY 17, 2021

Later during verification, an i-Vector extracted from a test utterance (about 15 second long) is compared against the enrolled i-Vector via a cosine similarity score. VoxCeleb1 dev test # of speakers 1,211 40 # of videos 21,819 677 # of utterances 148,642 4,874. The test set is used to evaluate model performance metrics.

Modeling 64

Modeling Testing Machine Learning Measurement 64

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. More Policies Emerged” (2010-2018).

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Birst BI

MAY 29, 2018

Today, BI vendors are already introducing AI capabilities in their products for data preparation, data discovery, and data science. Data from multiple sources was normally stored in silos, and research was typically presented in a fragmented, disjointed report that was open to interpretation.

Slice and Dice 74

Slice and Dice Analytics Business Intelligence Machine Learning 74

The Data Visualisation Catalogue

JANUARY 30, 2019

Today it is possible to manipulate data directions actually walk around data worlds. This allows users to make accurate data analysis and thus, faster decisions. Why VR Data Visualization Could Be Your Secret Weapon in 2018 , SMICHRISSOFT. Virtual reality allows us to do the same thing through data visualization.

Interactive 66

Interactive Visualization Big Data Technology 66

Hurwitz & Associates

MAY 21, 2019

New additions include: a Web Console to help administrators more easily manage multiple environments; a Universal Base Image (UBI) to help developers create pre-tested golden images for different container environments; and Insights for analytics on operations data. Impact on IBM Customers. Microsoft Windows workloads (e.g.

Software 40

Software Enterprise Machine Learning Management 40

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. Programmers have always developed tools that would help them do their jobs, from test frameworks to source control to integrated development environments. We’d like to see more companies test for fairness.

Enterprise 279

Enterprise Modeling Testing Reporting 279

Cloudera

SEPTEMBER 12, 2018

It was deeply gratifying to see so many organizations deploying the tools and techniques of data science and advanced analytics to solve difficult and important problems. I predict that next year’s competition will be even more amazing as we continue pushing the frontiers of data science forward. Cloud Success: .

Machine Learning 45

Machine Learning Big Data Data Science Data Warehouse 45

Cloudera

AUGUST 6, 2018

Only 3 years later, in 2018 the organization has received a total of 75 million messages. To manage what’s become one of the largest data sets on mental health and crisis in the world, Crisis Text Line had to be built from the ground up around technology and data. . For example, the Michael J.

Machine Learning 50

Machine Learning Internet of Things Cost-Benefit Data-driven 50

CIO Business Intelligence

APRIL 15, 2022

But according to the UK’s Turing Institute, a national center for data science and AI, the predictive tools made little to no difference. MIT Technology Review has chronicled a number of failures, most of which stem from errors in the way the tools were trained or tested. In a statement on Oct. In a statement on Oct.

Analytics 145

Analytics Machine Learning Insurance Testing 145

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. For example, we may prefer one model to generate a range, but use a second scenario-based model to “stress test” the range. Our team does a lot of forecasting.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

datapine

OCTOBER 21, 2020

Summing up the product of all this work, the data science team developed a web-based user interface that forecasts patient loads and helps in planning resource allocation by utilizing online data visualization that reaches the goal of improving the overall patients’ care. 2) Electronic Health Records (EHRs).

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364

Insight

JANUARY 14, 2020

Will a network trained with fake data be able to generalize to the real world? Lauren Holzbauer was an Insight Fellow in Summer 2018. And the winner is… Both implementations of our gym equipment classifier achieved 99% accuracy on the test set. The first time I walked into a weight room was six years ago, while I was at UCLA.

Metrics 58

Metrics Optimization Modeling Testing 58

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. The approach they’ve used applies to other popular data science APIs such as NumPy , Tensorflow , and so on.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Insight

MARCH 8, 2019

Insight is committed to helping more women launch careers in tech , so in celebration of International Women’s Day 2019, we wanted to share a few of the projects completed by women participating in the January 2019 Data Science and Health Data Science sessions. A team of four Fellows from our Silicon Valley programs?— ?Tayler

Data Science 75

Data Science Sales Machine Learning Reporting 75

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. 2018-06-21). back to the structure of the dataset. Let’s look through some antidotes.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Data Science and Beyond

OCTOBER 15, 2017

Do you know what data science is? Do you understand what data scientists do? Just so we’re on the same page, what is data science? 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.

Data Science 71

Data Science Deep Learning Machine Learning Data-driven 71

DataRobot

FEBRUARY 16, 2021

When DataRobot and Snowflake , the Data Cloud company, announced a new partnership in 2018, their stated goal was to “accelerate the adoption of AI in the enterprise.” DataRobot’s Automated Feature Discovery simplifies and accelerates this feature engineering process through the automation of expert data science best practices.

Machine Learning 52

Machine Learning Data Science Testing Modeling 52

Domino Data Lab

MARCH 16, 2021

2018) Simple meaningless data processing steps, may cause saliency methods to result in significant changes (Kindermans et al., Allows a researcher to test the importance of high-level, human interpretable concepts in their network. This is an exciting and important area of data science research.

Modeling 122

Modeling Deep Learning Testing Optimization 122

Alation

FEBRUARY 13, 2020

After 116 years in business, legendary guitar maker Gibson filed for bankruptcy in 2018. It requires organizations to adopt a scientific mindset of testing and iteration to find the truth, rather than using data to support a predetermined path. Sustainable innovation is often customer-centric if not customer-led.

Digital Transformation 59

Digital Transformation Insurance Data-driven Machine Learning 59

Insight

MAY 16, 2019

In this post, I describe how I built an object detection algorithm (FurniSure), during my time as an Insight Data Science Fellow, using a convolutional neural network-based algorithm called “You Only Look Once” to identify, classify, and localize different types of furniture in images and videos. Transfer Learning?—?YOLO. Precision?—?Recall

Deep Learning 84

Deep Learning Machine Learning Metadata Data Science 84

IBM Big Data Hub

FEBRUARY 22, 2024

IBM’s Scaled Data Science Method , an extension of CRISP-DM, offers governance across the AI model lifecycle informed by collaborative input from data scientists, industrial-organizational psychologists, designers, communication specialists and others. The CRISP-DM model is useful here. This is misguided.

Metadata 93

Metadata Measurement Risk Modeling 93

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

The Unofficial Google Data Science Blog

APRIL 23, 2024

Modeling live experiment data Data scientists at YouTube are rarely involved in the analysis of typical live traffic experiments. Multiparameter experiments, however, generate richer data than standard A/B tests, and automated t-tests alone are insufficient to analyze them well. Testing Statistical Hypotheses.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

IBM Big Data Hub

AUGUST 1, 2023

A specific kind of foundation model known as a large language model (LLM) is trained on vast amounts of text data for NLP tasks. An open-source model, Google created BERT in 2018. Dev Developers can write, test and document faster using AI tools that generate custom snippets of code.

Modeling 55

Modeling Cost-Benefit Data Lake Machine Learning 55

AWS Big Data

FEBRUARY 1, 2024

Filter data from the Common Crawl dataset As you can see from the create table SQL statement, there are several fields that can help filter the data. Using an EMR on EC2 cluster can help you carry out tests before submitting jobs to the production environment. You can use the image Data Science 2.0

Metadata 98

Metadata Modeling Data Processing Unstructured Data 98

Insight

FEBRUARY 13, 2019

In late 2018, Google open-sourced BERT, a powerful deep learning algorithm for natural language processing. BERT can be pre-trained on a massive corpus of unlabeled data, and then fine-tuned to a task for which you have a limited amount of data. Prior to Insight, he was at IBM Watson. Yay this is fun! Run training.

Testing 72

Testing Machine Learning Deep Learning Modeling 72

Insight

DECEMBER 18, 2019

Lauren Holzbauer was an Insight Fellow in Summer 2018. Second, it uses those weights to make a test prediction for each training instance and computes the sum of squared errors between the predictions and ground truth values (i.e. Get the theory behind neural networks straight once and for all! A 2-layer “vanilla” Neural Network.

Optimization 85

Optimization Machine Learning Testing Visualization 85

Domino Data Lab

OCTOBER 23, 2019

Eighty percent of this problem is collecting the data and then transforming the data. The other 20 percent is ML- and data science–related tasks like finding the right model, doing EDA, and feature engineering. Gathering the Data. there is a list of data sources to extract and transform. In Figure 6.1,

Statistics 59

Statistics Machine Learning Testing Modeling 59

Cloudera

NOVEMBER 14, 2018

Register for our webinar (Thursday November 15 2018). To train a machine learning model you usually need to move all the data to a single machine or, failing that, to a cluster of machines in a data center. It would be less costly for the manufacturer if its customers were to send it such data. Predictive maintenance.

Manufacturing 41

Manufacturing Machine Learning IoT Modeling 41

Domino Data Lab

AUGUST 22, 2019

Data scientists and researchers require an extensive array of techniques, packages, and tools to accelerate core work flow tasks including prepping, processing, and analyzing data. Utilizing NLP helps researchers and data scientists complete core tasks faster. Relative to extrinsic evaluations, intrinsic tests are quick.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

O'Reilly on Data

MAY 21, 2019

For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production. With all the hype around AI, it can be tempting to jump into use cases involving data types with which you aren’t familiar. Source: O'Reilly.

Machine Learning 243

Machine Learning Technology Deep Learning Data Science 243

CIO Business Intelligence

AUGUST 1, 2023

During keynotes and discussions with CIOs, I remind everyone how strategic priorities evolve significantly every two years or less, from growth in 2018, to pandemic and remote work in 2020, to hybrid work and financial constraints in 2022. That’s my key advice to CIOs and IT leaders.

Digital Transformation 98

Digital Transformation Unstructured Data Strategy Experimentation 98