O'Reilly on Data

JANUARY 25, 2021

Year-over-year (YOY) growth compares January through September 2020 with the same months of 2019. Let’s look at the data, starting at the highest level: O’Reilly online learning itself. Usage of O’Reilly online learning grew steadily in 2020, with 24% growth since 2019. AI, Machine Learning, and Data.

Machine Learning 362

Machine Learning Software Testing Technology 362

O'Reilly on Data

MAY 21, 2019

As the number of data scientists and machine learning engineers grow within an organization, tools have to be standardized, models and features need to be shared, and automation starts getting introduced. 58% of survey respondents indicated they are building or evaluating data science platforms. Data results from a Twitter poll.

Machine Learning 234

Machine Learning Technology Deep Learning Data Science 234

Business Over Broadway

JULY 29, 2020

Data professionals use a variety of data science tools, technologies and languages to help them get insights from data. Because data analysis is central to the gaining insights from data, we focus on tools that relate to analyzing data.

Statistics 92

Statistics Software Business Intelligence Data Science 92

IBM Big Data Hub

FEBRUARY 22, 2024

Recognizing this, the Department of Defense (DoD) launched the Joint Artificial Intelligence Center (JAIC) in 2019, the predecessor to the Chief Digital and Artificial Intelligence Office (CDAO), to develop AI solutions that build competitive military advantage, conditions for human-centric AI adoption, and the agility of DoD operations.

Metadata 95

Metadata Measurement Risk Modeling 95

Business Over Broadway

JANUARY 19, 2021

Nearly half of data professionals surveyed in Kaggle’s 2020 Data Science and Machine Learning Survey said they do not use BI tools. The top tool used by data professionals to analyze data are local development environments (48%), followed by basic statistical software (30%). Top Tools Used to Analyze Data.

Business Intelligence 85

Business Intelligence Analytics Statistics Machine Learning 85

DataRobot

NOVEMBER 12, 2021

Although teams are starting to adopt third-party tools for deployment, 46 percent of survey respondents are not using a market-tested tool for deploying AI. That’s a risky business, as constructing AI models from scratch requires countless hours of time and effort, and the results may incorporate biased data and inappropriate algorithms.

Cost-Benefit 98

Cost-Benefit Machine Learning Sales ROI 98

CIO Business Intelligence

NOVEMBER 20, 2023

Take AVA, the AI-infused customer support bot that AirAsia introduced in 2019. Using generative AI as a part of the chatbot creation process is one of the most promising use cases at present, and certainly the least risky,” says Benedikt Schönhense, co-founder and head of data science at Springbok AI.

Interactive 122

Interactive Risk ROI Testing 122

TIBCO

MARCH 22, 2021

For more on what to expect, check out the highlights from TAF 2019 on the TAF community homepage. Products discussed will include TIBCO Spotfire ® , TIBCO ® Data Science, TIBCO ® Streaming, TIBCO ® Data Virtualization, TIBCO EBX , TIBCO WebFOCUS ® , and more.

Analytics 97

Analytics Manufacturing Digital Transformation Data Science 97

Data Science 101

MAY 6, 2019

So it was a natural transition for me to move to a career that felt like it had higher impact, a wide variety of work, and good career opportunity—and data science was that was that move for me. We pulled questions from some of our Springboard students and this one is from Miguel, who is in our data science vertical.

Data Science 98

Data Science Modeling Machine Learning Testing 98

O'Reilly on Data

DECEMBER 12, 2019

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. It’s a very simple and powerful idea: simulate data that you find interesting and see what a model predicts for that data. 6] Debugging may focus on a variety of failure modes (i.e.,

Machine Learning 187

Machine Learning Modeling Testing Risk Management 187

Smart Data Collective

DECEMBER 11, 2020

Big data is changing the future of software development in countless ways. Towards Data Science talked about some of the biggest changes that big data has created in this rapidly evolving field. One of them was the shift towards all-in-one data-driven software development across various industries.

Data-driven 100

Data-driven Software Big Data Testing 100

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. back to the structure of the dataset. Let’s look through some antidotes. Ergo, less interpretable.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

DataRobot

JUNE 29, 2021

Machine learning models trained on 2019 data didn’t know what to do. Above image shows a DataRobot MLOps retraining policy set to trigger when data drift occurs. As part of the same process, it also generates and tests a whole host of new models and presents the top ones as recommended challengers. Over and over.

Machine Learning 80

Machine Learning Data Processing Forecasting Modeling 80

CIO Business Intelligence

MAY 17, 2022

But it’s not just science fiction writers who are worried about the dangers of uncontrolled AI. In a 2019 survey by Emerj , an AI research and advisory company, 14% of AI researchers said that AI was an “existential threat” to humanity. This particular hospital’s data science team had built a system to identify such comorbidities.

Risk 144

Risk Consulting Machine Learning Data Science 144

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

DataRobot

JUNE 2, 2021

Although MLOps has historically been concerned with IT-centric operational issues such as machine learning model testing, deployment, and monitoring, it is increasingly clear that the best MLOps solutions address the entire machine learning lifecycle and support all participants involved in the journey from data to value with AI.

Experimentation 52

Experimentation Machine Learning Reporting Modeling 52

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. In 2019, Netflix alone released 371 new TV shows and movies.

Risk 67

Risk ROI Modeling Metrics 67

Data Science and Beyond

APRIL 5, 2021

The Australian bushfires of 2019-20 provided me with extra motivation to help nudge Automattic to do more in the fight against climate change. The initial covid-19 lockdown provided me with extra free time to make the measurement and offsetting of Automattic’s emissions from data centre power use happen. Only time will tell.

Experimentation 61

Experimentation Testing Publishing Measurement 61

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

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

Smarten

MAY 18, 2022

Which sales representative sold the most pancake mix during April 2015 to May 2019? Who sold the most cake in Phoenix, Arizona in the last quarter of 2019? With context-driven searching, the sales manager can ask all kinds of questions to test theories and hypotheses. Sample Date Range Question. Sample Absolute Time Question.

Data-driven 67

Data-driven Sales Metrics Testing 67

AWS Big Data

JUNE 6, 2023

In order to mature our data marts, it became clear that we needed to provide Analysts and other data consumers with all tracked digital analytics data in our DWH as they depend on it for analyses, reporting, campaign evaluation, product development and A/B testing. It was great for quick iteration over a new feature.

Analytics 55

Analytics Data Lake Testing Optimization 55

Smart Data Collective

OCTOBER 14, 2019

Regardless of if you’re a data science professional or an IT department who wants to help your company have more successful data science projects, it’s essential to have some data science tools under your belt to avail of when needed. Tools to Help Your Data Science Projects Excel.

Data Science 67

Data Science Machine Learning Big Data Interactive 67

Insight

SEPTEMBER 20, 2019

Segmentation Since a few patients had multiple images in the dataset, the data were separated, by patient, into three parts: training (80%), validation (10%), and testing (10%). The box plot below shows a summary of the testing results. The results of the testing dataset are shown in the following confusion matrix.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

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. Sci Foo 2019.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Smarten

MAY 11, 2017

The Smarten Advanced Data Discovery gives users the freedom to leverage data beyond simple visual data analysis and dashboards. Advanced Data Discovery allows business users to perform early prototyping and to test hypothesis without the skills of a data scientist, ETL or developer.

Experimentation 49

Experimentation Visualization Business Intelligence Predictive Analytics 49

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

BizAcuity

MARCH 31, 2022

By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Source: Gartner Research). Source: TCS).

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

CIO Business Intelligence

MARCH 8, 2023

According to Infosys research, data and artificial intelligence (AI) could generate $467 billion in incremental profits worldwide and become the cornerstone of enterprises gaining a competitive edge. Yet even with all these potential inhibitors, it’s clear the appetite for AI is growing and spend is increasing with it.

Enterprise 52

Enterprise Data Governance Data Strategy Testing 52

Alation

FEBRUARY 13, 2020

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. The companies that succeed in the age of digital transformation are reinventing themselves and embracing a customer data culture.

Digital Transformation 59

Digital Transformation Insurance Data-driven Machine Learning 59

Sisense

FEBRUARY 24, 2021

And while organizations are trying to bridge the skills gap by hiring data scientists, data analysts, and data engineers, some are giving these highly technical individuals a seat in the C-suite in the form of the chief data officer (CDO). The role of the chief data officer.

Data Warehouse 69

Data Warehouse Big Data Metrics Visualization 69

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

bridgei2i

SEPTEMBER 1, 2020

in March and April compared with 2019. BRIDGEi2i’s Data Science expertise, portfolio of AI-powered solutions, and consumer industry context have helped enterprises build customer loyalty, drive incremental sales growth, get more value for marketing spend, and enhance supply chain planning and operation through AI Accelerators.

Sales 52

Sales Metrics Optimization Enterprise 52

Insight

DECEMBER 19, 2019

Typically D would be a training or test dataset that contains a number of different images and the set ? Typically, the performance would only be measured on a test set which is a subset of X. Anton Muehlemann was an Insight Fellow during our Summer 2019 session. would be the set of all sets of images. Recall that ?

Machine Learning 74

Machine Learning Measurement Modeling Testing 74

KDnuggets

JULY 30, 2019

This article is designed to give you a full picture from constructing a hypothesis testing to understanding p-value and using that to guide our decision making process.

Testing 85

Testing Statistics Data Science 85

Insight

APRIL 16, 2019

This free, full-time, 7 week fellowship based in San Francisco will start in September 2019. Fellows will join a network of ambitious software engineers, systems engineers, IT professionals, and data analysts who share common goals, but wield a diverse set of complementary skills.

Machine Learning 68

Machine Learning Software Risk Reporting 68

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

For example, consider the following simple example fitting a two-dimensional function to predict if someone will pass the bar exam based just on their GPA (grades) and LSAT (a standardized test) using the public dataset (Wightman, 1998). Curiosities and anomalies in your training and testing data become genuine and sustained loss patterns.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108