IBM Big Data Hub

APRIL 22, 2024

We believe there are three core areas that every organization should focus on: sustainability strategy and reporting; energy transition and climate resilience; and intelligent asset, facility and infrastructure management. Using AI, business teams can “clean” data, manage through gaps, and report across different frameworks.

IoT 80

IoT Internet of Things Cost-Benefit Reporting 80

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. billion in 2022, according to a research study published by The Insight Partners in August 2022.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

CIO Business Intelligence

OCTOBER 4, 2023

A volatile market Over 28% of skills and certifications changed in market value from April 1 through July 1 (the period covered by Foote Partners’ Q3 report), a far greater number than the 19% quarterly average over the last 24 months. The premium it attracts rose by more than 10%, making it the fastest-rising AI-related certification.

Prescriptive Analytics 134

Prescriptive Analytics IT Machine Learning Risk 134

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

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. A foundational data analysis tool is Statistics , and everyone intuitively applies it daily. So, what do these terms really mean?

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

Cloudera

FEBRUARY 25, 2021

However, only 4% of enterprise executives today report seeing success from their ML investment. AMPs are produced by Cloudera Fast Forward Labs, a team of ML/AI Research Engineers focused on making the recently possible in machine learning practical and usable by business today. Deep Learning for Image Analysis.

Deep Learning 81

Deep Learning Machine Learning Forecasting Visualization 81

bridgei2i

FEBRUARY 21, 2020

In fact, statistics from Maryville University on Business Data Analytics predict that the US market will be valued at more than $95 billion by the end of this year. Deep learning provides an edge over your competition. AI Adoption is becoming increasingly rampant among B2B companies. IoT Continues to Boom.

IoT 83

IoT Analytics Deep Learning B2B 83

O'Reilly on Data

APRIL 19, 2021

The percentage of respondents reporting “mature” practices has been roughly the same for the last few years. This is almost exactly in line with the results from 2020, where 25% of the respondents reported that they had products in production (“Mature” wasn’t a possible response in the 2020 survey.). Asia has clearly caught up.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

Domino Data Lab

OCTOBER 7, 2020

Statistical methods for analyzing this two-dimensional data exist. This statistical test is correct because the data are (presumably) bivariate normal. When there are many variables the Curse of Dimensionality changes the behavior of data and standard statistical methods give the wrong answers. Data Has Properties.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

Smart Data Collective

MAY 8, 2022

From the statistics shown, this means that both AI and big data have the potential to affect how we work in the workplace. Above all, there needs to be a set methodology for data mining, collection, and structure within the organization before data is run through a deep learning algorithm or machine learning.

Big Data 105

Big Data Data Analytics Analytics Cost-Benefit 105

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.” Generative AI uses advanced machine learning algorithms and techniques to analyze patterns and build statistical models.

Enterprise 122

Enterprise Modeling Testing Data-driven 122

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. They send out reports and dashboards.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

FineReport

DECEMBER 19, 2019

For the super rookie, the learning cost and threshold are relatively low, and it is easy to get started. Taking FineReport as an example, it is a BI reporting tool that can connect to various data sources, quickly analyze the data, and make various reports and cool dashboards. It can produce a variety of complex reports.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

IBM Big Data Hub

AUGUST 11, 2023

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. MLOps is the next evolution of data analysis and deep learning. MLOps enables greater transparency and faster response to such requests.

Data Science 56

Data Science Machine Learning Cost-Benefit Deep Learning 56

O'Reilly on Data

JULY 28, 2020

Many companies face a problem that’s even worse: no one knows which levers contribute to the metrics that impact business outcomes, or which metrics are important to the company (such as those reported to Wall Street by publicly-traded companies). It’s easy to focus on the wrong metric if you haven’t done the proper research.

Marketing 362

Marketing Experimentation Metrics Testing 362

Sisense

APRIL 15, 2021

An ML user with statistics training and some basic knowledge of how deep learning neural networks operate can start with columns of revenue and annuity and generate additional features including mean, standard deviation, and kurtosis to enhance the model training data and thus improve prediction accuracy.

Analytics 98

Analytics Data Science Modeling Machine Learning 98

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. Nearly all respondents reported promising early results from gen AI experiments and planned to increase their spending in 2024 to support production workloads.

Cost-Benefit 93

Cost-Benefit Modeling Manufacturing Interactive 93

O'Reilly on Data

DECEMBER 12, 2019

The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8]. If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. Currency amounts reported in Taiwan dollars.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

Jedox

JULY 31, 2018

First-generation EPM software tools enabled normal business users to view their data from various angles and store it safely in a database specialized for flexible planning, analytics, and reporting. It runs statistics and algorithms (also known as data mining) on masses of historical data to calculate probabilities and future events.

Technology 44

Technology Prescriptive Analytics Machine Learning Business Intelligence 44

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Cloudera

NOVEMBER 3, 2021

Thanks to pioneers like Andrew NG and Fei-Fei Li, GPUs have made headlines for performing particularly well with deep learning techniques. Today, deep learning and GPUs are practically synonymous. While deep learning is an excellent use of the processing power of a graphics card, it is not the only use.

Deep Learning 115

Deep Learning Machine Learning Data Science Cost-Benefit 115

Smarten

APRIL 19, 2024

The Current State of AI in Analytics By combining machine learning with AI, analytics vendors can and have made strides in providing user-friendly, self-serve augmented analytics products that include the newest versions of these technologies: Machine Learning (ML) Generative Artificial Intelligence (GenAI) Deep Learning Natural Language Processing (..)

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Domino Data Lab

APRIL 21, 2021

Auxiliary techniques like relying on card holders to report fraudulent transactions have unfortunately proven to be ineffective [1]. In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data. deep learning) there is no guaranteed explainability.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

DataRobot

NOVEMBER 9, 2021

Signal classification models are typically built using time series principles; traditionally used features that include central, windowed, lag, and lead statistics can do the job but sometimes there might be scenarios where we want to eke out more performance out of the data. Image courtesy towardsAI.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

CONTACT Software

FEBRUARY 19, 2019

In line with this, Gartner has now published a “ Magic Quadrant for Data Science and Machine Learning Platforms “ The document itself can only be viewed behind a paywall, but on the net some of the companies mentioned in the report offer access to the document by entering the address.

Data Science 40

Data Science Statistics Machine Learning Deep Learning 40

datapine

NOVEMBER 19, 2019

Internal comms: Computer vision technology can serve to improve internal communication by empowering employees to perform their tasks more visually, sharing image-based information that is often more digestible and engaging than text-based reports or information alone. Artificial Intelligence (AI).

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

MARCH 3, 2019

We had big surprises at several turns and have subsequently published a series of reports. Let’s look through some of the insights gained from those reports. Seriously, this entire article merely skims the surface of those reports. The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Smart Data Collective

OCTOBER 14, 2019

Ludwig is a tool that allows people to build data-based deep learning models to make predictions. For example, there are financial charts, which could work well when showing year-end reports. It works like a fully functional spreadsheet, which means there is not a large learning curve to navigate when starting to use it.

Data Science 67

Data Science Machine Learning Big Data Interactive 67

Domino Data Lab

MAY 8, 2019

For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

MAY 21, 2019

Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. Machine learning is not only appearing in more products and systems, but as we noted in a previous post , ML will also change how applications themselves get built in the future.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

Domino Data Lab

JULY 9, 2019

When I showed up I was reporting to the head of BI who reported to CTO who reported to CIO who reported to EVP of digital products who reported to CEO. At this point data is a function that reports directly to CEO. We are solidly on state and in particular, we are in a subgroup called data.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

MARCH 24, 2020

Understanding the importance of general automation and democratization of all parts of the DS/ML/AI workflow, it’s important to recognize that we’ve done pretty well at democratizing data collection and gathering, modeling [8] , and data reporting [9] , but what remains stubbornly difficult is the whole process of preparing the data.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346

O'Reilly on Data

JANUARY 25, 2021

In this report, we look at the data generated by the O’Reilly online learning platform to discern trends in the technology industry—trends technology leaders need to follow. Look at all the angst heating up social media when TIOBE or RedMonk releases their reports on language rankings. AI, Machine Learning, and Data.

Machine Learning 363

Machine Learning Software Testing Technology 363

Smart Data Collective

MAY 19, 2021

This trend is prevalent in the US, UK and further afield, with the former’s Bureau of Labour Statistics reporting that three of the jobs with the highest forecast growth level are wind turbine technician, registered nurse, and solar technician.

Data Analytics 89

Data Analytics Analytics Big Data Predictive Analytics 89