datapine

MAY 14, 2019

2) “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courville. Best for: This best data science book is especially effective for those looking to enter the data-driven machine learning and deep learning avenues of the field. 4) “Machine Learning Yearning” by Andrew Ng.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

Occam's Razor

MARCH 23, 2021

Finally, few analytics teams obsess about predictive analytics in a way that allows them to dictate future action. This time around, my goal was for the analytics team to chart a very different path… To solve for expansive influence, before, during, after, money is spent by the organization. Analytics on the Edge.

Analytics 131

Analytics Scorecard Strategy Testing 131

Business Over Broadway

MARCH 13, 2019

IBM is using the power of its Watson Studio platform to extend the power of AI to people who fall outside the realm of data science, machine learning and AI experts. IBM Watson Studio is an end-to-end analytics solution to help you gain insights from your data. To view the statistics, click on the Statistics Node and hit run.

Statistics 78

Statistics Measurement Descriptive Analytics Machine Learning 78

IBM Big Data Hub

AUGUST 7, 2023

AI algorithms have the potential to surpass traditional statistical approaches for analyzing comprehensive recruitment data and accurately forecasting enrollment rates. AI empowers real-time site performance monitoring and forecasting by automating data analysis, providing timely alerts and insights, and enabling predictive analytics.

Optimization 57

Optimization Forecasting Data-driven Strategy 57

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. Data science is an interdisciplinary field within STEM that combines math and statistics, computer science, and business acumen to find patterns in complex datasets that can be used to improve decision making. None of these techniques are new.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Data Science 101

OCTOBER 31, 2019

A definition from the book ‘Data Mining: Practical Machine Learning Tools and Techniques’, written by, Ian Witten and Eibe Frank describes Data mining as follows: “ Data mining is the extraction of implicit, previously unknown, and potentially useful information from data. Regression.

Data mining 77

Data mining KDD Data Science Forecasting 77

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning? temperature, salary).

Machine Learning 77

Machine Learning Modeling Deep Learning Predictive Modeling 77

Birst BI

AUGUST 23, 2018

A key goal of AI or machine learning automation is to have machines complete tasks for you, freeing up time so you can focus on the more complex, higher-value tasks. 1] Until then, we observe in another Gartner survey that organizations are outsourcing various tasks in the Machine Learning pipeline. [2].

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

datapine

JANUARY 6, 2022

More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Let’s quickly review the most common statistical terms: Mean: a mean represents a numerical average for a set of responses. Standard deviation: this is another statistical term commonly appearing in quantitative analysis.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

BizAcuity

MAY 16, 2022

Fast food companies like Domino’s, McDonald’s and KFC collect massive amounts of data which includes customer data and other key business metrics for their own operations. While visual analytics serves almost the same purpose but with a different and more sophisticated approach. That was in the 1900’s.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. He was saying this doesn’t belong just in statistics. Tukey did this paper.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. What Is Business Intelligence And Analytics?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

datapine

AUGUST 29, 2022

Whether you are a complete novice or a seasoned BI professional, you will find here some books on data analytics that will help you cultivate your understanding of this essential field. James Warren, on the other part, is a successful analytics architect with a background in machine learning and scientific computing.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Corinium

APRIL 25, 2019

Life insurance needs accurate data on consumer health, age and other metrics of risk. For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. And more recently, we have also seen innovation with IOT (Internet Of Things).

Insurance 150

Insurance Risk IoT Cost-Benefit 150

CIO Business Intelligence

JANUARY 26, 2023

Tracking costs is just one small part of a system that is constantly gathering statistics and watching for anomalies. AppDynamics also offers a proprietary machine learning engine to turn historical data into a plan for efficient deployment. Currently available for AWS and Azure.

Management 116

Management Forecasting Dashboards Optimization 116

DataRobot Blog

NOVEMBER 8, 2022

In a world that is increasingly outcome-focused and platform-based, we have integrated strategy and predictive analytics to move at the speed of our clients’ decisions and established a scalable framework for uncovering and acting on insights in an organized, simple, and transparent operating model.

Predictive Analytics 59

Predictive Analytics Marketing Analytics Data-driven 59

datapine

NOVEMBER 27, 2019

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. Industries harness predictive analytics in different ways.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 4, 2019

Predictive & Prescriptive Analytics. Predictive Analytics: What could happen? We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. Approaches need to take this dynamic nature into mind.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Smarten

APRIL 11, 2018

Gartner defines a Citizen Data Scientist as ‘a person who creates or generates models that leverage predictive or prescriptive analytics but whose primary job function is outside of the field of statistics and analytics.’ Comfortable with metrics, measurements and prioritization.

Analytics 40

Analytics Prescriptive Analytics Business Intelligence ROI 40

Smarten

DECEMBER 3, 2023

‘Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation and insight explanation to augment how people explore and analyze data in analytics and BI platforms. What is self-service analytics?

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Alation

MAY 2, 2023

Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience. Meanwhile, predictive analytics enable them to analyze customer market trends.

Data Analytics 52

Data Analytics Analytics ROI Data Governance 52

Alation

JANUARY 27, 2022

Analytics can identify patterns that depict risks, opportunities, and trends. And historical data can be used to inform predictive analytic models, which forecast the future. The insights gained from analytics can provide value to businesses in several ways. What Is the Value of Analytics?

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

Alation

MAY 2, 2023

Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience. Meanwhile, predictive analytics enable them to analyze customer market trends.

Data Analytics 40

Data Analytics Analytics ROI Data Governance 40

Andrew White

JANUARY 11, 2021

The data suggests several things: The work of traditional analytics and BI continues towards democratization in the business unit directly, we call this domain analytics in our research, part of domain D&A. See: Tool: A Living Library of Real-World Data and Analytics Use Cases. We do have good examples and bad examples.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

MAY 1, 2023

Business End-User Benefits Embedding analytics into essential applications makes analytics more pervasive. As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. Visual Analytics Users are given data from which they can uncover new insights.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52