KDnuggets

NOVEMBER 4, 2021

Toloka is a crowdsourced data labeling platform that handles data collection and annotation projects for machine learning at any scale. In this Nov 11 Live Demo, Learn how to get reliable training data for machine learning.

Machine Learning 102

Machine Learning Data Collection 102

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.

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

Domino Data Lab

MAY 15, 2019

Machine Learning Projects are Hard: Shifting from a Deterministic Process to a Probabilistic One. Over the years, I have listened to data scientists and machine learning (ML) researchers relay various pain points and challenges that impede their work. Product Management for Machine Learning.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

Rocket-Powered Data Science

JULY 6, 2021

Specifically, in the modern era of massive data collections and exploding content repositories, we can no longer simply rely on keyword searches to be sufficient. Labeling, indexing, ease of discovery, and ease of access are essential if end-users are to find and benefit from the collection.

Strategy 266

Strategy Machine Learning Metadata Knowledge Discovery 266

Smart Data Collective

JUNE 20, 2019

. My colleagues and I at Smart Data Collective have written extensively about the benefits of big data in fields like marketing, hospitality and cybersecurity. We sometimes realize that we need to discuss the implications of big data for other fields as well. How does machine learning influence technical writing?

Machine Learning 68

Machine Learning Big Data Statistics Data Collection 68

Smart Data Collective

OCTOBER 30, 2019

Machine learning is changing the future of marketing in many beneficial ways. There are a number of tactics that marketers can pursue to optimize campaigns with machine learning algorithms. Use artificial intelligence tools that rely on machine learning to optimize content for different visitors.

Machine Learning 72

Machine Learning Advertising Big Data Marketing 72

CIO Business Intelligence

APRIL 12, 2024

These roles include data scientist, machine learning engineer, software engineer, research scientist, full-stack developer, deep learning engineer, software architect, and field programmable gate array (FPGA) engineer.

Deep Learning 124

Deep Learning IT Machine Learning IoT 124

Data Science and Beyond

JANUARY 23, 2016

Many modern data scientists don’t get to experience data collection in the offline world. Recently, I spent a month sailing down the northern Great Barrier Reef, collecting data for the Reef Life Survey project.

Data Collection 52

Data Collection Machine Learning 52

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

Rocket-Powered Data Science

JUNE 17, 2022

Here is a list of my top moments, learnings, and musings from this year’s Splunk.conf : Observability for Unified Security with AI (Artificial Intelligence) and Machine Learning on the Splunk platform empowers enterprises to operationalize data for use-case-specific functionality across shared datasets.

Machine Learning 237

Machine Learning Recreation/Entertainment Risk Business Objectives 237

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. Machine learning adds uncertainty.

Management 338

Management Machine Learning Experimentation Metrics 338

Analytics Vidhya

MAY 29, 2023

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Both are associated with data usage but differ from each other.

Data mining 294

Data mining Data Collection Strategy Data Analytics 294

O'Reilly on Data

DECEMBER 10, 2019

Roughly a year ago, we wrote “ What machine learning means for software development.” Karpathy suggests something radically different: with machine learning, we can stop thinking of programming as writing a step of instructions in a programming language like C or Java or Python. Instead, we can program by example.

Software 263

Software Machine Learning Risk Data-driven 263

TDAN

AUGUST 17, 2021

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

Predictive Modeling 115

Predictive Modeling Modeling Data mining Big Data 115

Smart Data Collective

AUGUST 11, 2022

Sustaining the responsible use of machines. Human labeling and data labeling are however important aspects of the AI function as they help to identify and convert raw data into a more meaningful form for AI and machine learning to learn. However, Ai uses algorithms that can screen and handle large data sets.

Data Quality 127

Data Quality Machine Learning Digital Transformation Big Data 127

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

O'Reilly on Data

NOVEMBER 13, 2019

Questions of ethics and what role it should play are increasingly arising in machine learning and AI research, especially in the area of science applications.

Machine Learning 187

Machine Learning Data Collection Modeling IT 187

CIO Business Intelligence

OCTOBER 24, 2023

With AI systems often reliant on vast amounts of data, ensuring this data remains private is a significant concern. AI can steal your IP—and generate new IP for you to protect Machine learning algorithms can be trained to reverse-engineer patented technologies. This raises legal and ethical implications.

Risk 126

Risk Recreation/Entertainment Data Collection Data Processing 126

Cloudera

FEBRUARY 8, 2021

In addition, moving outside the vehicle, existing fragmented approaches for data management associated with the machine learning lifecycle are limiting the ability to deploy new use cases at scale. The vehicle-to-cloud solution driving advanced use cases.

Machine Learning 107

Machine Learning Manufacturing Unstructured Data Modeling 107

Smart Data Collective

APRIL 5, 2022

They are using tools like Amazon SageMaker to take advantage of more powerful machine learning capabilities. Amazon SageMaker is a hardware accelerator platform that uses cloud-based machine learning technology. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks.

Cost-Benefit 120

Cost-Benefit Machine Learning Data Science Unstructured Data 120

Smart Data Collective

JUNE 8, 2023

The introduction of data collection and analysis has revolutionized the way teams and coaches approach the game. Liam Fox, a contributor for Forbes detailed some of the ways that data analytics is changing the NFL. Big data will become even more important in the near future.

Data Analytics 80

Data Analytics Analytics Data Collection Statistics 80

Cloudera

APRIL 13, 2022

It means your company has automated the processes of collecting, understanding and acting on data across the board, from production to purchasing to product development to understanding customer priorities and preferences. Data collection and interpretation when purchasing products and services can make a big difference.

Data Collection 107

Data Collection Machine Learning Strategy Data-driven 107

Smart Data Collective

MAY 29, 2023

With these changes comes the challenge of understanding how to gather, manage, and make sense of the data collected in various markets. With the introduction and use of machine learning, AI tech is enabling greater efficiencies with respect to data and the insights embedded in the information.

Data Collection 74

Data Collection Big Data Statistics Software 74

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. Top 15 data science bootcamps. Data Science Dojo. Data Science Dojo.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. Alex Ratner on “Creating large training data sets quickly”.

Machine Learning 263

Machine Learning Data Quality Statistics Modeling 263

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

DataRobot

APRIL 27, 2021

As organizations start getting back to normal after the COVID-19 pandemic, AI and machine learning is top of mind for many of these leaders. Now this market is looking at embedding AI and machine learning together with automations to drive more end-to-end solutions and tackle those potential use cases that were once thought impossible.

Machine Learning 98

Machine Learning Cost-Benefit Predictive Modeling Software 98

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

APRIL 27, 2023

Artificial intelligence and machine learning (AI/ML) were not advanced enough to accurately capture, organize, and interpret the data to make accurate recommendations. Machine learning has also greatly advanced over the past several years. There were also limitations in technology.

Management 98

Management Internet of Things Cost-Benefit Uncertainty 98

CIO Business Intelligence

MARCH 30, 2022

For organizations looking to move beyond stale reports, decision intelligence holds promise, giving them the ability to process large amounts of data with a sophisticated mix of tools such as artificial intelligence and machine learning to transform data dashboards and business analytics into more comprehensive decision support platforms.

Machine Learning 144

Machine Learning Risk Testing Data-driven 144

CIO Business Intelligence

APRIL 1, 2022

There is no need to pre-process data, train or hypertune machine learning models, nor load balance or manually provision your infrastructure to handle unpredictable traffic spikes. For Forrester’s senior analyst Tracy Woo, Google’s intent is to gain more market share while also gaining access to more data.

IT 111

IT Machine Learning Cost-Benefit Data Collection 111

Smart Data Collective

AUGUST 2, 2022

This figure is expected to grow as more companies recognize the potential and decide to increase the resources they dedicate to machine learning and predictive analytics tools. They have also used machine learning to automate the transportation of important materials. Big data. AI-based software development.

Software 124

Software Machine Learning B2B Manufacturing 124

CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science gives the data collected by an organization a purpose. Data science vs. data analytics.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

Smart Data Collective

DECEMBER 7, 2020

Since the market for big data is expected to reach $243 billion by 2027 , savvy business owners will need to find ways to invest in big data. Artificial intelligence is rapidly changing the process for collecting big data, especially via online media. The Growth of AI in Web Data Collection.

Data Quality 75

Data Quality Data Collection Big Data Machine Learning 75

Smart Data Collective

DECEMBER 17, 2021

The process of Marketing Analytics consists of data collection, data analysis, and action plan development. Understanding your marketing data to make more informed and successful marketing strategy decisions is a systematic process. Types of Data Used in Marketing Analytics. Source: [link].

Marketing Analytics 92

Marketing Analytics Marketing Data-driven Analytics 92

Smart Data Collective

MARCH 29, 2021

Asset data collection. Data has become a crucial organizational asset. Companies need to make the most out of their data resources, which includes collecting and processing them correctly. Data collection and processing methods are predicted to optimize the allocation of various resources for MRO functions.

Big Data 136

Big Data Management Cost-Benefit Internet of Things 136

Smart Data Collective

OCTOBER 16, 2023

Smart devices use sensors to collect data and upload it to the Internet. Examples include CCTV records, automated vacuum cleaners, weather station data, and other sensor-generated data. All in all, big data refers to massive data collections obtained from various sources.

Big Data 100

Big Data IoT Cost-Benefit Advertising 100