IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

IBM Big Data Hub

DECEMBER 19, 2023

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

Machine Learning 70

Machine Learning Optimization Unstructured Data Sales 70

Rocket-Powered Data Science

JULY 6, 2023

These AI applications are essentially deep machine learning models that are trained on hundreds of gigabytes of text and that can provide detailed, grammatically correct, and “mostly accurate” text responses to user inputs (questions, requests, or queries, which are called prompts). Guess what? It isn’t.

Statistics 152

Statistics Deep Learning Machine Learning Modeling 152

Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Business Over Broadway

FEBRUARY 14, 2021

Machine learning algorithms are employed by data professionals to predict important outcomes as well as find patterns and structure in their data. The application of machine learning reaches across industries (e.g., Top Machine Learning Algorithms Used in 2020. Data Engineer (3 used).

Machine Learning 106

Machine Learning Data Science Reporting Marketing 106

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

DataRobot Blog

JULY 28, 2022

Rapid advances in machine learning in recent years have begun to lower the technical hurdles to implementing AI, and various companies have begun to actively use machine learning. As a DataRobot data scientist , I have worked with team members on a variety of projects to improve the business value of our customers.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Rocket-Powered Data Science

JULY 19, 2023

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

DataRobot Blog

MARCH 16, 2023

This integration takes the power of one of the most advanced large language model technologies that exists today in Azure OpenAI Service, and through DataRobot, drives value-centric outcomes with machine learning. The integration allows you to generate intelligent data science code that reflects your use case.

Data Science 98

Data Science Technology Data-driven Modeling 98

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. This blog post provides a concise session summary, a video, and a written transcript. data science’s emergence as an interdisciplinary field – from industry, not academia. He was saying this doesn’t belong just in statistics.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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 are Data Scientists?

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

O'Reilly on Data

SEPTEMBER 15, 2021

64% of the respondents took part in training or obtained certifications in the past year, and 31% reported spending over 100 hours in training programs, ranging from formal graduate degrees to reading blog posts. To nobody’s surprise, our survey showed that data science and AI professionals are mostly male. Salaries by Gender.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

Smarten

APRIL 25, 2024

By providing business users with the right solution, you can ensure dependable data quality and offer your users valuable data insight that will support good business decisions. Users can harness the power of statistics and machine learning to uncover hidden insights and improve the overall quality of your data.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

Data Science and Beyond

DECEMBER 31, 0001

This website/blog is mostly meant to group together stuff I write in various places. It’s mainly focused on data science. I’m an experienced data scientist and software engineer with a strong background in computer science, programming, machine learning, and statistics.

Statistics 52

Statistics Forecasting Machine Learning Data Science 52

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 87

Metrics Machine Learning Risk Statistics 87

CIO Business Intelligence

OCTOBER 13, 2023

It’s a role that requires experience with natural language processing , coding languages, statistical models, and large language and generative AI models. According to the survey, 28% of respondents said they have hired data scientists to support generative AI, while 30% said they have plans to hire candidates.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Smarten

JANUARY 30, 2024

Business users cannot even hope to prepare data for analytics – at least not without the right tools. Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation?

Analytics 67

Analytics Data Quality Visualization Metadata 67

Aryng

OCTOBER 18, 2022

Typically, a data scientist is considered as someone who uses statistical methods, machine learning, and AI approaches to solve problems, spending their day using tools like python or R using pre-existing libraries to […] The post Mythbuster: Only Data Scientists Can Analyze Data appeared first on Aryng's Blog.

Statistics 52

Statistics Machine Learning IT Data Science 52

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. A background in (or a firm grasp of) data warehousing and mining. BI engineer.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

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. To solve practical decision problems, the Data Scientist typically uses combinations of these methods.

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

Cloudera

FEBRUARY 25, 2021

Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. Cloudera has a front-row seat to organizational challenges as those enterprises make Machine Learning a core part of their strategies and businesses.

Deep Learning 82

Deep Learning Machine Learning Forecasting Visualization 82

Rita Sallam

APRIL 2, 2023

We explored these questions and more at our Bake-Offs and Show Floor Showdowns at our Data and Analytics Summit in Orlando with 4,000 of our closest D&A friends and family. The first featured analytics and BI platform Gartner Magic Quadrant leaders while the other showcased high interest data science and machine learning platforms.

Optimization 52

Optimization Machine Learning Insurance Risk 52

Sisense

APRIL 10, 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. NLP can be used on written text or speech data.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

IBM Big Data Hub

FEBRUARY 13, 2024

Like diligent students, these generative models soak up information and identify patterns, structures and relationships between data points, which is how they learn the grammar of poetry, artistic brushstrokes and musical melodies. Imagine each data point as a glowing orb placed on a vast, multi-dimensional landscape.

Enterprise 124

Enterprise Modeling Testing Data-driven 124

Cloudera

SEPTEMBER 10, 2021

By more effectively leveraging its petabytes of current and historical data, the IRS is working to stave off costly fraud and waste, more efficiently deliver on fundamental missions, and better protect taxpayers, including from risks such as identity theft. Visit our website or view our recent industry event featuring the IRS and Nvidia.

Machine Learning 66

Machine Learning Statistics Data-driven Big Data 66

Smarten

OCTOBER 13, 2022

Listen to the Experts: Citizen Data Scientist Results are Real! Gartner has predicted that, ‘a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.’

Data Science 52

Data Science Statistics Consulting Machine Learning 52

Ontotext

DECEMBER 15, 2023

It includes only ML papers and related entities; this SPARQL query shows some statistics: papers tasks models datasets methods evaluations repos 376557 4267 24598 8322 2101 52519 153476 We can start with these repositories (most of them are on Github) and get all their topics. We can start with a connecting dataset like LinkedPapersWithCode.

Machine Learning 69

Machine Learning Interactive Deep Learning Statistics 69

DataRobot Blog

MAY 23, 2022

Department of Transportation Data. Example of border transport data from USDOT. Department of Transportation (USDOT) Bureau of Transportation Statistics (BTS) provide publicly-available monthly summary statistics for both the U.S.-Canada The database contains entry data from Mexico to the U.S. Canada and U.S.-Mexico

Forecasting 59

Forecasting Statistics Machine Learning Modeling 59

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

The Unofficial Google Data Science Blog

NOVEMBER 19, 2015

by SEAN GERRISH If you are a regular at this blog, thanks for reading. We will continue to bring you posts from the range of data science activities at Google. We briefly highlight some of the things we look for in data scientists we hire at Google and give tips on ways to prepare. This post is different. Be passionate.

Statistics 75

Statistics Data Science Machine Learning Sales 75

Smarten

MAY 31, 2022

The augmented analytics solution your business chooses must have a complete set of predictive analytical techniques with built-in, sophisticated algorithms and tools that are easy to use and will guide the user to choose the right predictive analytical technique for the data they are analyzing. Descriptive Statistics. Forecasting.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 80

Machine Learning Modeling Deep Learning Predictive Modeling 80

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Occam's Razor

MARCH 30, 2017

Machine Learning | Marketing. Machine Learning | Analytics. People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Most Deep Learning methods involve artificial neural networks, modeling how our bran works.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

IBM Big Data Hub

MARCH 7, 2023

From the moment of birth to discharge, healthcare professionals can collect so much data about an infant’s vitals—for instance, heartbeat frequency or every rise and drop in blood oxygen level. The worldwide statistics on premature births are staggering— the University of Oxford estimates that neonatal sepsis causes 2.5

Risk 52

Risk Technology Informatics Predictive Modeling 52

IBM Big Data Hub

AUGUST 7, 2023

Therefore, IBM observes that more clients tend to consult AI leaders to help establish governance and enhance AI and data science capabilities, an operating model in the form of co-delivery partnerships. The post Optimizing clinical trial site performance: A focus on three AI capabilities appeared first on IBM Blog.

Optimization 58

Optimization Forecasting Data-driven Strategy 58