Cloudera

SEPTEMBER 10, 2020

Cloudera has been named a Leader in The Forrester Wave : Notebook-Based Predictive Analytics and Machine Learning, Q3 2020. We are honored to receive recognition as a leader from Forrester for Cloudera Machine Learning (CML) — our enterprise machine learning experience for Cloudera Data Platform (CDP).

Machine Learning 95

Machine Learning Predictive Analytics Analytics Enterprise 95

Analytics Vidhya

JANUARY 11, 2021

ArticleVideos This article was published as a part of the Data Science Blogathon. Introduction Many times we wonder if predictive analytics has the. The post AlgoTrading using Technical Indicator and ML models appeared first on Analytics Vidhya.

Modeling 295

Modeling Predictive Analytics Data Science Publishing 295

Smarten

APRIL 10, 2023

Leverage Enterprise Investments for Predictive Analytics and Gain Numerous Advantages! Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Why the focus on predictive analytics?

Predictive Analytics 52

Predictive Analytics Predictive Modeling Analytics Prescriptive Analytics 52

Smart Data Collective

JANUARY 27, 2021

Machine learning technology has made cryptocurrency investing opportunities more lucrative than ever. The impact of machine learning on the market for bitcoin and other cryptocurrencies is multifaceted. Importance of machine learning in forecasting cryptocurrency prices.

Machine Learning 139

Machine Learning Forecasting Predictive Analytics Marketing 139

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 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

Cloudera

APRIL 9, 2021

The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization. And this blog will focus on Predictive Analytics. Data Collection – streaming data. Data Enrichment – data engineering. The ML Challenge.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Smart Data Collective

DECEMBER 9, 2020

When most people consider the merits of machine learning, they typically think about its applications from a capitalist standpoint. There are countless ways that business owners are using machine learning advances to pad their bottom lines. They learn to identify numerous risk factors and alert the driver.

Machine Learning 141

Machine Learning Risk Insurance Predictive Analytics 141

Smarten

MAY 31, 2022

When combined with Citizen Data Scientist initiatives, the adoption and use of predictive modeling and forecasting techniques can be a boon to any enterprise. Team members who have access to augmented analytics and assisted predictive modeling can plan better, predict more accurately and dependably meet goals and objectives.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Cloudera

OCTOBER 14, 2020

Not many other industries have such a sophisticated business model that encompasses a culture of streamlined supply chains, predictive maintenance, and unwavering customer satisfaction. Step 1: Using the training data to create a model/classifier. Fig 2: Diagram showing how CML is used to build ML training models.

Machine Learning 98

Machine Learning Modeling Cost-Benefit Testing 98

Smart Data Collective

MARCH 27, 2023

Unleash your analytical prowess in today’s most coveted professions – Data Science and Data Analytics! As companies plunge into the world of data, skilled individuals who can extract valuable insights from an ocean of information are in high demand.

Data Science 93

Data Science Statistics Data-driven Machine Learning 93

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

Smart Data Collective

NOVEMBER 25, 2020

Machine learning is transforming the financial sector more than anybody could have ever predicted. One of the most significant changes brought by advances in machine learning is with the loan underwriting process. Towards Data Science analyzed several dozen papers on the use of machine learning in loan scoring.

Machine Learning 144

Machine Learning Risk Predictive Analytics Forecasting 144

CIO Business Intelligence

JUNE 29, 2022

Machine learning operations (MLOps) analysts have burst onto the scene as demand has grown among businesses for consistent, reliable insights in-house. In essence, MLOps analysts are a section of the data science team. Our role is to make machine learning, or AI, projects more systematic, repeatable, and well maintained.

Data Science 90

Data Science Machine Learning Data-driven Predictive Analytics 90

Smart Data Collective

JUNE 18, 2021

Machine learning technology has been instrumental to the future of the criminal justice system. We have previously talked about the role of predictive analytics in helping solve crimes. However, big data has also led to some concerns with racial profiling and other biases.

Predictive Analytics 69

Predictive Analytics Forecasting Analytics Big Data 69

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

Smart Data Collective

NOVEMBER 18, 2020

You should learn what a big data career looks like , which involves knowing the differences between different data processes. Online courses and universities are offering a growing number of programs of study that center around the data science specialty. What is Data Science? Machine learning.

Data mining 143

Data mining Data Science Informatics Statistics 143

Smart Data Collective

NOVEMBER 14, 2019

They have refined their data decision-making approaches to include new predictive analytics models to forecast trends and adapt to evolving customer behavior. They have developed analytics models to address looming changes in the dynamic industry.

Predictive Analytics 79

Predictive Analytics Analytics Forecasting Modeling 79

Cloudera

JULY 18, 2018

As such, we are witnessing a revolution in the healthcare industry, in which there is now an opportunity to employ a new model of improved, personalized, evidence and data-driven clinical care. Additionally, organizations are increasingly restrained due to budgetary constraints and having limited data sciences resources.

Machine Learning 52

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 52

DataRobot Blog

JANUARY 27, 2019

In my previous articles Predictive Model Data Prep: An Art and Science and Data Prep Essentials for Automated Machine Learning, I shared foundational data preparation tips to help you successfully. by Jen Underwood. Read More.

Machine Learning 92

Machine Learning Modeling Predictive Modeling Predictive Analytics 92

O'Reilly on Data

MAY 1, 2019

Watch highlights from expert talks covering machine learning, predictive analytics, data regulation, and more. People from across the data world are coming together in London for the Strata Data Conference. Making data science useful. Watch " Making data science useful.".

Advertising 188

Advertising Machine Learning Predictive Analytics Data-driven 188

CIO Business Intelligence

JUNE 7, 2022

To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? Data analytics methods and techniques.

Data Analytics 133

Data Analytics Diagnostic Analytics Management Analytics 133

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

Rocket-Powered Data Science

MARCH 19, 2021

The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. One CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. A lot has changed in those five years, and so has the data landscape.

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

Smarten

MARCH 18, 2019

Data Science and Predictive Analytics Made Simple! Imagine a world where data science and predictive analytics tools are created for business users!

Predictive Analytics 40

Predictive Analytics Visualization Software Analytics 40

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. The online program includes an additional nonrefundable technology fee of US$395 per course.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

DataRobot Blog

MARCH 8, 2023

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. In our world of Big Data, marketers no longer need to simply rely on their gut instincts to make marketing decisions.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

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. Data Science Techniques.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Smarten

DECEMBER 17, 2018

Tools like Assisted Predictive Modeling allow the average business user to become a Citizen Data Scientist with tools that offer guidance and auto-suggestions to help the user arrive at the outcome they need without being frustrated or having to call in an army of analysts and IT staff to help them complete their analysis.

Predictive Analytics 40

Predictive Analytics Predictive Modeling Analytics Statistics 40

Domino Data Lab

JANUARY 24, 2019

In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. Over the last couple years, it would be hard to blame anyone for being overwhelmed looking at the data science platform market landscape. Proprietary (often GUI-driven) data science platforms.

Data Science 65

Data Science Marketing Data-driven Statistics 65

IBM Big Data Hub

JULY 25, 2018

Data science and machine learning provide the basis for business growth, cost and risk reduction and even new business model creation -- but implementing predictive analytics does present some challenges.

Data Science 53

Data Science Visualization Predictive Analytics Machine Learning 53

Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

Decision Management Solutions

MARCH 25, 2019

Nancy Casbarro and Deb Zawisa of Novarico recently published a new paper on Data Science in Insurance: Expansion and Key Issues subscription required) that was summarized in this nice little article on Dig-in 3 challenges facing insurers in data science implementation. 2 – Attracting talent.

Insurance 75

Insurance Data Science Testing Modeling 75

Rocket-Powered Data Science

MARCH 10, 2020

And this: perhaps the most powerful node in a graph model for real-world use cases might be “context”. How does one express “context” in a data model? Hence, the graph model can be applied productively and effectively in numerous network analysis use cases. Ahh, that’s the topic for another article.

Metadata 250

Metadata Machine Learning ROI Prescriptive Analytics 250

Smarten

SEPTEMBER 14, 2018

Just Simple, Assisted Predictive Modeling for Every Business User! You can’t get a business loan, join with a business partner, successfully bid on a project, open a new location, hire the right employees or plan for the future without predictive analytics.

Predictive Modeling 40

Predictive Modeling Business Analytics Modeling Analytics 40

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 137

Data mining Data-driven Statistics OLAP 137