Laminar Security

DECEMBER 13, 2023

In the ever-evolving digital landscape, the importance of data discovery and classification can’t be overstated. As we generate and interact with unprecedented volumes of data, the task of accurately identifying, categorizing, and utilizing this information becomes increasingly difficult.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

O'Reilly on Data

DECEMBER 10, 2019

Roughly a year ago, we wrote “ What machine learning means for software development.” In that article, we talked about Andrej Karpathy’s concept of Software 2.0. In short, we can use machine learning to automate software development itself. It’s time to evaluate what has happened in the year since we wrote that article.

Software 259

Software Machine Learning Risk Data-driven 259

O'Reilly on Data

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. If you’re an AI product manager (or about to become one), that’s what you’re signing up for.

Marketing 361

Marketing Experimentation Metrics Testing 361

Smart Data Collective

MARCH 16, 2022

Last year, in an article that talked about the impact big data has on finance, we said that location data sets can make investing easier. A large portion of this market is driven by investment companies and mutual funds. Today, we are going to look at the potential influence big data has on personal finance in detail.

Big Data 103

Big Data Deep Learning Finance Data-driven 103

Ontotext

DECEMBER 15, 2023

This post describes our approach to developing such a taxonomy by integrating and coreferencing data from numerous sources. The official (first) repo is tensorflow/tensor2tensor that has topics: machine-learning reinforcement-learning deep-learning machine-translation tpu. And so the snowball rolls!

Machine Learning 69

Machine Learning Interactive Deep Learning Statistics 69

Smart Data Collective

MARCH 27, 2023

billion on AI in 2021 , but small businesses may spend even more on AI-driven financial management software. They have also started integrated computer vision and deep learning technology to identify inefficiencies. Many small businesses are investing in AI-driven financial management software.

Software 87

Software Finance Cost-Benefit Data-driven 87

O'Reilly on Data

JUNE 7, 2022

That’s an allusion to the debate ( sometimes on Twitter ) between LeCun and Gary Marcus, who has argued many times that combining deep learning with symbolic reasoning is the only way for AI to progress. (In What additional data would a large language model need to avoid making these mistakes?

Modeling 363

Modeling Interactive Optimization Deep Learning 363

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

Experimentation 74

Experimentation Modeling Deep Learning Data-driven 74

CIO Business Intelligence

APRIL 27, 2022

As a technology company you can imagine how easy it is to think of data-first modernization as a technology challenge. Data fabric, data cleansing and tagging, data models, containers, inference at the edge – cloud-enabled platforms are all “go-to” conversation points. The Experience Agenda. The Platforms Agenda.

Strategy 129

Strategy Data-driven Internet of Things Measurement 129

Smart Data Collective

MARCH 1, 2022

Furthermore, in this article, we will discuss how far machine learning and AI have come and directly affected the improvement of voice technology. . How machine learning is improving voice technology. Google’s Wavenet: a learning model used to generate audio recordings. Data is fuel. Smarter audio.

Machine Learning 99

Machine Learning Technology Deep Learning Marketing 99

Smarten

APRIL 19, 2024

In this article, we will discuss the current state of AI in analytics, as well as the future of this burgeoning industry and how it can be applied to analytics to simplify and clarify results and to make analytics easier for businesses and business users to leverage. It must be integrated with business systems to leverage available data.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Domino Data Lab

DECEMBER 17, 2019

This article provides concise insights into GANs to help data scientists and researchers assess whether to investigate GANs further. Unsurprisingly, this mainstream attention may also lead to data scientists and researchers fielding questions about, or assessing, whether to leverage GANs in their own workflows. Introduction.

Deep Learning 64

Deep Learning Machine Learning Modeling Statistics 64

O'Reilly on Data

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. Why: Data Makes It Different.

IT 342

IT Testing Experimentation Software 342

O'Reilly on Data

FEBRUARY 18, 2020

O’Reilly online learning contains information about the trends, topics, and issues tech leaders need to watch and explore. It’s also the data source for our annual usage study, which examines the most-used topics and the top search terms. [1]. Within the data topic, however, ML+AI has gone from 22% of all usage to 26%.

Data-driven 331

Data-driven Software Statistics Marketing 331

Occam's Razor

MARCH 30, 2017

Perhaps you now see why I’ve pivoted my career to Storytelling with data over the last couple of years. :). Invest in continuous learning. The most conservative estimate is that AI driven changes are expected to replace 25% of jobs across the world, by 2026. Deep Learning is a specific ML technique.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

Machine Learning 55

Machine Learning Data Science Statistics Deep Learning 55

BizAcuity

MARCH 31, 2022

There have been so many articles published about AI and its applications, you can find millions of articles from broad concepts to deep technical literature on the internet. You must be tired of continuously hearing quotes like, ‘data is the new oil’ and what not. AI Adoption and Data Strategy. Source: TCS).

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Data Science and Beyond

DECEMBER 23, 2018

In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning. However, I’ve found it hard to apply what I’ve learned about causal inference to my work. I’ve been interested in the area of causal inference in the past few years.

Deep Learning 103

Deep Learning Experimentation Data-driven Data Science 103

IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Demystifying generative AI At the heart of Generative AI lie massive databases of texts, images, code and other data types.

Enterprise 119

Enterprise Modeling Testing Data-driven 119

Ontotext

FEBRUARY 26, 2024

This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. RED’s focus on news content serves a pivotal function: identifying, extracting, and structuring data on events, parties involved, and subsequent impacts.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences that alienate consumers and businesses. This includes trust in the data, the security, the brand and the people behind the AI.

B2B 65

B2B Interactive Optimization Forecasting 65

Cloudera

SEPTEMBER 20, 2022

The state of the art in AI systems for artistic tasks almost universally use deep-learning models, which presuppose a significant amount of compute resources both to create them, and once created to continue to use them for producing images. Data — where does it come from? Access — who can use it?

Deep Learning 87

Deep Learning Cost-Benefit Risk Data-driven 87

IBM Big Data Hub

SEPTEMBER 27, 2023

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content. All this reduces the risk of a data leak or unauthorized access.

Risk 93

Risk Modeling Cost-Benefit Enterprise 93

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. In other words, using metadata about data science work to generate code. Introduction. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Smart Data Collective

APRIL 3, 2020

Big data is driving a number of changes in the business community. Some of the benefits of big data incredibly obvious. However, there are also a lot of other benefits big data creates that don’t get as much publicity. One of the biggest benefits of big data is that it can create giveaway bots for online businesses.

Big Data 93

Big Data Data-driven Data mining Software 93

Smart Data Collective

APRIL 3, 2020

Big data is driving a number of changes in the business community. Some of the benefits of big data incredibly obvious. However, there are also a lot of other benefits big data creates that don’t get as much publicity. One of the biggest benefits of big data is that it can create giveaway bots for online businesses.

Big Data 79

Big Data Data-driven Data mining Software 79

Domino Data Lab

OCTOBER 14, 2020

Guest post by Jeff Melching, Distinguished Engineer / Chief Architect Data & Analytics. We’ve developed a model-driven software platform, called Climate FieldView , that captures, visualizes, and analyzes a vast array of data for farmers and provides new insight and personalized recommendations to maximize crop yield.

Experimentation 99

Experimentation Modeling Deep Learning Testing 99

CIO Business Intelligence

APRIL 15, 2022

In 2017, The Economist declared that data, rather than oil, had become the world’s most valuable resource. Organizations across every industry have been and continue to invest heavily in data and analytics. But like oil, data and analytics have their dark side. The algorithm learned to identify children, not high-risk patients.

Analytics 140

Analytics Machine Learning Insurance Testing 140

Sisense

APRIL 15, 2021

Your company is gathering data (and has likely been doing so for years), and you’ve probably got a system or two to glean insights from that data to make smarter decisions. Whatever you do and however you do it, augmented analytics serve up deeper intelligence from data with less heavy lifting. Analytics is the future.

Analytics 98

Analytics Data Science Modeling Machine Learning 98

Sisense

MAY 26, 2020

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. Today, text data is everywhere. can’t” becomes “can not”).

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

Data Science and Beyond

OCTOBER 15, 2017

Aspiring data scientists and other visitors to this site often repeat the same questions. How do I become a data scientist? Before we get into it, have you thought about why you want to become a data scientist? Why should I become a data scientist? Do you know what data science is? It depends on your situation.

Data Science 71

Data Science Deep Learning Machine Learning Data-driven 71

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. Its value is so significant that scaling data science has become the new business imperative with organizations spending tens of millions of dollars on data, technology and talent. What is Data Science and How is it Used?

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Occam's Razor

AUGUST 28, 2017

Over the last couple years, I’ve spent an increasing amount of time diving into the possibilities Deep Learning (DL) offers in terms of what we can do with Artificial Intelligence (AI). These learnings go back to the robot and improve its chances of success. And, I could not be more excited to see them out in the world.

Deep Learning 139

Deep Learning Machine Learning Marketing Strategy 139

DataRobot Blog

DECEMBER 20, 2022

In this article, we’ll showcase the ability of AI to improve the quality of the potential investment’s future performance, with a specific example from the real estate segment. In this article, we’ll first take a closer look at the concept of Real Estate Data Intelligence and the potential of AI to become a game changer in this niche.

Management 59

Management Machine Learning Optimization Modeling 59

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. Introduction. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JUNE 23, 2019

Skomoroch advocates that organizations consider installing product leaders with data expertise and ML-oriented intuition (i.e., Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. It is similar to R&D.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Years and years of practice with R or "Big Data." I read articles they write. Intro to Machine Learning. Machine Learning. Deep Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136