CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Smart Data Collective

SEPTEMBER 16, 2020

These statistical models are growing as a result of the wide swaths of available current data as well as the advent of capable artificial intelligence and machine learning. Deep Learning, Machine Learning, and Automation. From a predictive analytics standpoint, you can be surer of its utility.

Predictive Analytics 139

Predictive Analytics Analytics Predictive Modeling Data mining 139

CIO Business Intelligence

JANUARY 19, 2024

The US Bureau of Labor Statistics (BLS) forecasts employment of data scientists will grow 35% from 2022 to 2032, with about 17,000 openings projected on average each year. You need experience in machine learning and predictive modeling techniques, including their use with big, distributed, and in-memory data sets.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

CIO Business Intelligence

JANUARY 25, 2024

That doesn’t mean getting certifications in deep learning or mastering natural language processing. We need people with a natural affinity for statistics, data patterns, and forecasting,” she says. “If If you start with that deep understanding, then you can use AI to do much more at a larger scale.”

Deep Learning 115

Deep Learning Cost-Benefit Statistics Manufacturing 115

Cloudera

FEBRUARY 25, 2021

They require a deep enough knowledge of dozens of ML techniques in order to choose the right approach for a given use case, a thorough understanding of everything required to execute on that use case, as well as a solid foundation in statistics fundamentals to ensure their choices and implementations are mathematically sound and appropriate.

Deep Learning 84

Deep Learning Machine Learning Visualization Forecasting 84

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. Monotonic Deep Lattice Networks Deep learning is a powerful tool when we have an abundance of data to learn from.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

datapine

NOVEMBER 19, 2019

AI refers to the autonomous intelligent behavior of software or machines that have a human-like ability to make decisions and to improve over time by learning from experience. Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI.

Technology 279

Technology Internet of Things IT IoT 279

Sisense

APRIL 15, 2021

For example, a user with some basic insight into why data preparation — the first of the four main steps in ML mentioned above — is important to training an ML model will ensure greater accuracy in the forecasting outcomes generated by the model.

Analytics 98

Analytics Data Science Machine Learning Modeling 98

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

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 118

Enterprise Testing Modeling Data-driven 118

IBM Big Data Hub

DECEMBER 19, 2023

Common machine learning algorithms for supervised learning include: K-nearest neighbor (KNN) algorithm : This algorithm is a density-based classifier or regression modeling tool used for anomaly detection. Regression modeling is a statistical tool used to find the relationship between labeled data and variable data.

Machine Learning 64

Machine Learning Optimization Unstructured Data Sales 64

Jedox

JULY 31, 2018

It runs statistics and algorithms (also known as data mining) on masses of historical data to calculate probabilities and future events. Modern-day forecasting, for example, relies heavily on predictive analysis. Types of Artificial Intelligence: Machine Learning, Deep Learning. Simply put, it is extremely(!)

Technology 44

Technology Prescriptive Analytics Machine Learning Business Intelligence 44

IBM Big Data Hub

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Supervised machine learning Supervised machine learning is a type of machine learning where the model is trained on a labeled dataset (i.e.,

Machine Learning 73

Machine Learning Modeling Deep Learning Predictive Modeling 73

DataRobot Blog

MAY 26, 2022

These methods provided the benefit of being supported by rich literature on the relevant statistical tests to confirm the model’s validity—if a validator wanted to confirm that the input predictors of a regression model were indeed relevant to the response, they need only to construct a hypothesis test to validate the input.

Risk 52

Risk Modeling Metrics Business Objectives 52

O'Reilly on Data

JULY 28, 2020

This tradeoff between impact and development difficulty is particularly relevant for products based on deep learning: breakthroughs often lead to unique, defensible, and highly lucrative products, but investing in products with a high chance of failure is an obvious risk.

Marketing 364

Marketing Experimentation Metrics Testing 364

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 98

Data Analytics Analytics Big Data Predictive Analytics 98

CIO Business Intelligence

MAY 6, 2025

Predictive analytics: Turning insight into foresight Predictive analytics uses historical data and statistical models or machine learning algorithms to answer the question, What is likely to happen? Predictive analytics: Seeing whats next Predictive analytics uses patterns in historical data to forecast future outcomes.

Prescriptive Analytics 78

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 78