O'Reilly on Data

APRIL 19, 2021

During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. The second-most significant barrier was the availability of quality data. Relatively few respondents are using version control for data and models. Respondents.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. Pragmatically, machine learning is the part of AI that “works”: algorithms and techniques that you can implement now in real products. We won’t go into the mathematics or engineering of modern machine learning here.

Management 363

Management Machine Learning Experimentation Metrics 363

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. In general terms, a model is a series of algorithms that can solve problems when given appropriate data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

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

CIO Business Intelligence

MAY 20, 2022

Artificial Intelligence (AI) is a fast-growing and evolving field, and data scientists with AI skills are in high demand. If you want to grow your data scientist career and capitalize on the demand for the role, you might consider getting a graduate degree in AI. University of California–Berkeley.

Machine Learning 145

Machine Learning Statistics Recreation/Entertainment Data Science 145

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. The simplest answer is that these terms refer to some of the many analytic methods available to Data Scientists.

Statistics 84

Statistics Machine Learning Deep Learning Sales 84

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Predict the impact of new policies, laws, and regulations on businesses and markets.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

CIO Business Intelligence

JANUARY 25, 2024

With two decades of experience as a human resources leader, Deepa Subbaiah, a senior director for HR at Freshworks, has deep expertise in exploring how enterprise teams can get the most out of workplace tech, from first-generation SaaS applications in the early 2000s to today’s AI-powered chatbots. Make it appealing and relevant to me.”

Deep Learning 115

Deep Learning Cost-Benefit Statistics Manufacturing 115

CIO Business Intelligence

JANUARY 26, 2024

Artificial Intelligence (AI) is a fast-growing and evolving field, and data scientists with AI skills are in high demand. If you want to grow your data scientist career and capitalize on the demand for the role, you might consider getting a graduate degree in AI.

Machine Learning 105

Machine Learning Statistics Recreation/Entertainment Data Science 105

datapine

NOVEMBER 19, 2019

No matter if you need to conduct quick online data analysis or gather enormous volumes of data, this technology will make a significant impact in the future. AI refers to the autonomous intelligent behavior of software or machines that have a human-like ability to make decisions and to improve over time by learning from experience.

Technology 279

Technology Internet of Things IT IoT 279

Smart Data Collective

JANUARY 13, 2022

The marketing profession has been fundamentally changed due to advances in artificial intelligence and big data. Unfortunately, there are a number of AI-driven marketing mistakes companies continue to make. For example, deep learning can be used to understand speech and also respond with speech.

Machine Learning 139

Machine Learning Cost-Benefit Marketing Deep Learning 139

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 Science Data-driven 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 118

Enterprise Testing Modeling Data-driven 118

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. Why Is Modeling Important?

Modeling 64

Modeling IT Deep Learning Risk Management 64

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

Smart Data Collective

AUGUST 20, 2021

As we said in the past, big data and machine learning technology can be invaluable in the realm of software development. Machine learning technology has become a lot more important in the app development profession. You need to know how to leverage machine learning algorithms appropriately.

Machine Learning 90

Machine Learning Data mining Advertising Deep Learning 90

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

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 Machine Learning Modeling 98

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 54

Machine Learning Data Science Statistics Deep Learning 54

IBM Big Data Hub

APRIL 22, 2024

To drive real change, it’s crucial for individuals, industries, organizations and governments to work together, using data and technology to uncover new opportunities that will help advance sustainability initiatives across the globe. The world is behind on addressing climate change.

IoT 77

IoT Internet of Things Cost-Benefit Reporting 77

CONTACT Software

FEBRUARY 19, 2019

The idea of platforms for automatic data analysis comes at just the right time. However, data science is not an area where you can magically get ahead with a tool or even a platform. A look at data science online tutorials from top providers like Coursera underlines the importance of these – well – down-to-earth tools.

Data Science 40

Data Science Statistics Machine Learning Deep Learning 40

Domino Data Lab

MAY 8, 2019

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Machine learning model interpretability. ML model interpretability and data visualization.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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

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. has 260,491 topics and is 15 levels deep.

Machine Learning 69

Machine Learning Deep Learning Interactive Statistics 69

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. It must be integrated with business systems to leverage available data. This approach does demand skills, data curation, and significant funding, but it will serve the market for third-party, specialized models.

Analytics 59

Analytics Predictive Modeling KPI Machine Learning 59

bridgei2i

OCTOBER 7, 2020

To catch up, underwriting which typically involved manual involvement in garnering data from documents has to change radically. Sometimes due to excessive volume of data, an underwriter can get confused and is unable to measure risk appropriately. Importance of capturing market data for optimized pricing models.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

IBM Big Data Hub

AUGUST 11, 2023

The advancement of computing power over recent decades has led to an explosion of digital data, from traffic cameras monitoring commuter habits to smart refrigerators revealing how and when the average family eats. Both computer scientists and business leaders have taken note of the potential of the data. How the models are stored.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

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

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. Why is high-quality and accessible data foundational?

Machine Learning 364

Machine Learning Statistics Data Quality Modeling 364

Analytics Vidhya

APRIL 24, 2024

Introduction Data science is an interdisciplinary field encompassing statistics, mathematics, programming, and domain knowledge to derive insights and knowledge from it. But it can become overwhelming for beginners […] The post Top 8 Coding Platforms for Data Science Beginners appeared first on Analytics Vidhya.

Data Science 316

Data Science Statistics Data-driven Marketing 316

Smart Data Collective

NOVEMBER 9, 2022

As a result of the activity of artificial intelligence, the machine learns, remembers, and reproduces the correct option. ML opens up new opportunities for computers to solve tasks previously performed by humans and trains the computer system to make accurate predictions when inputting data. Top ML Companies.

Machine Learning 122

Machine Learning Testing Cost-Benefit Data-driven 122

CIO Business Intelligence

APRIL 2, 2025

Whether in process automation, data analysis or the development of new services AI holds enormous potential. The spectrum is broad, ranging from process automation using machine learning models to setting up chatbots and performing complex analyses using deep learning methods. Model and data analysis.

Consulting 64

Consulting Data-driven Machine Learning Optimization 64