CIO

FEBRUARY 16, 2024

It’s all about the data In order to unleash the power of your data, it needs to be AI-ready. That means moving your data into a dynamic cloud environment as well as consolidating data from the multiple sources where it is kept around the business. Unleashing data with generative AI Fixing this problem is paramount.

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O'Reilly Media - Data

JUNE 21, 2018

The O’Reilly Data Show Podcast: Andrew Burt and Steven Touw on how companies can manage models they cannot fully explain. In this episode of the Data Show , I spoke with Andrew Burt , chief privacy officer at Immuta , and Steven Touw , co-founder and CTO of Immuta. Continue reading Managing risk in machine learning models.

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CIO

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

Analytics 338

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O'Reilly Media - Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. 1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. Model decay : ML models and data pipelines are notoriously “brittle.” [5]

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CIO

JUNE 7, 2024

-based company, which claims to be the top-ranked supplier of renewable energy sales to corporations, turned to machine learning to help forecast renewable asset output, while establishing an automation framework for streamlining the company’s operations in servicing the renewable energy market.

Energy 321

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TechBeacon

NOVEMBER 2, 2021

Despite widespread interest in machine learning (ML), relatively few projects leave the proof-of-concept phase and enter production.

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Artificial Inteligence Machine Learning Report Organization 144

Mentormate

MAY 31, 2023

In this article, we will discuss how MentorMate and our partner eLumen leveraged natural language processing (NLP) and machine learning (ML) for data-driven decision-making to tame the curriculum beast in higher education. Here, we will primarily focus on drawing insights from structured and unstructured (text) data.

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CIO

MAY 14, 2024

In past years, reporting fatal drug overdoses has largely been a paper- and human-driven process in King County, which shares the information with state and federal agencies. Seattle, the county seat, reported nearly 600 drug overdose deaths in 2022, an increase of 72% from the previous year.

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Cloudera

APRIL 9, 2021

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

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CIO

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making.

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DataRobot

JANUARY 17, 2023

As a data scientist, one of the best things about working with DataRobot customers is the sheer variety of highly interesting questions that come up. Peek into our conversation to learn when machine learning does—and doesn’t—work well in financial markets use cases. For price discovery (e.g., For price discovery (e.g.,

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Cloudera

FEBRUARY 11, 2022

Advances in the development and application of Machine Learning (ML) and Deep Learning (DL) algorithms, require greater care to ensure that the ethics embedded in previous rule-based systems are not lost. What is Machine Learning. Instead, they are learned by training a model on data.

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Netflix Tech

NOVEMBER 11, 2022

Data analysis and machine learning techniques are great candidates to help secure large-scale streaming platforms. We present a systematic overview of the unexpected streaming behaviors together with a set of model-based and data-driven anomaly detection strategies to identify them.

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CIO

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data 331

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CIO

MAY 21, 2024

“We know the keys to realizing the full power of AI revolve around two important things: applying AI to a well-defined, practical business issue, and leveraging high quality data,” said Epicor chief product and technology officer Vaibhav Vohra, in a statement. Epicor is putting its R&D efforts into AI and data management.

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CIO

JULY 26, 2023

The only thing we have on premise, I believe, is a data server with a bunch of unstructured data on it for our legal team,” says Grady Ligon, who was named Re/Max’s first CIO in October 2022. And the crew is using AWS SageMaker machine learning (ML) to give its agents the best local leads and prospective buyers.

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CIO

JULY 28, 2022

For the past few years, IT leaders at a US financial services company have been struggling to hire data scientists to harness the increasing flood of incoming data that, if used properly, could improve customer experience and drive new products. It’s exponentially harder when it comes to data scientists.

Data 359

Data Artificial Inteligence Machine Learning Fractional CTO 359

CIO

APRIL 12, 2024

According to a report from Indeed , a large part of this shift has come as organizations focus more on adopting AI in the workplace. Even as the IT job market experiences shifting dynamics, employment website Indeed reports a range of roles have maintained resiliency and even grown in demand.

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TechCrunch

APRIL 16, 2021

Peter Wang is CEO and co-founder of data science platform Anaconda. By 2025, 463 exabytes of data will be created each day, according to some estimates. However, in our collective infatuation with data (and obtaining more of it), what’s often overlooked is the role that storytelling plays in extracting real value from data.

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TechCrunch

OCTOBER 28, 2021

As companies gather ever-growing sets of data, finding issues with that data that could impact the viability of a machine learning model becomes increasingly important. Anomalo is putting machine learning to work to help solve the data viability issue automatically.

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CIO

JUNE 10, 2024

Moreover, many need deeper AI-related skills, too, such as for building machine learning models to serve niche business requirements. He wants data scientists who can build, train, and validate models for use cases, and who can perform exploratory analysis and hypothesis testing. Case in point: Training data workers on AI bias.

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Openxcell

MARCH 30, 2023

From human genome mapping to Big Data Analytics, Artificial Intelligence (AI),Machine Learning, Blockchain, Mobile digital Platforms (Digital Streets, towns and villages),Social Networks and Business, Virtual reality and so much more. What is Machine Learning? What is IoT or Internet of Things?

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CIO

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. Manufacturing: Predict the location and rate of machine failures.

Analytics 363

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Hacker Earth Developers Blog

MAY 22, 2020

In our third episode of Breaking 404 , we caught up with Srivatsan Ramanujam, Director of Software Engineering: Machine Learning, Salesforce to discuss everything about Machine Learning and the best practices for ML engineers to excel in their careers. Again, focus on Data Science and Machine Learning.

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Hacker Earth Developers Blog

DECEMBER 26, 2018

Banks have always been custodian of customer data, but they lack the technological and analytical capability to derive value from the data. On the other hand, fintech companies have the analytical capabilities and, thanks to payments services directives, they now have access to valuable data.

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Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

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CIO

MARCH 24, 2023

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

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Palo Alto Networks

JUNE 1, 2023

And then the rest of us on the team support those analysts by enabling tooling, logging — giving them the alert data and the insights they need in order to be successful.” ChatGPT, a language-based machine learning model, is not exempt from this discussion. There are certain groups that trend year over year. Want to dig in more?

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CIO

NOVEMBER 14, 2022

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions.

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System Artificial Inteligence Data Analysis 361

Altexsoft

JULY 23, 2020

When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. More time for development of new models.

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Artificial Inteligence Machine Learning DevOps Tools 145

Altexsoft

MAY 12, 2022

Today, we have AI and machine learning to extract insights, inaudible to human beings, from speech, voices, snoring, music, industrial and traffic noise, and other types of acoustic signals. But first, let’s go over the basics: What is the audio analysis, and what makes audio data so challenging to deal with. What is audio data?

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Altexsoft

JUNE 29, 2021

In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. The role of a machine learning engineer in the data science team.

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CIO

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.

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CIO

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

Trends 363

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TechCrunch

JANUARY 2, 2022

Most artificial intelligence models are trained through supervised learning, meaning that humans must label raw data. Data labeling is a critical part of automating artificial intelligence and machine learning model, but at the same time, it can be time-consuming and tedious work. ScreenShot | AIMMO website.

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