Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ It is meant to identify crucial relationships and opportunities and risks and help the organization to accurately predict: Growth.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

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

DataRobot Blog

JULY 28, 2022

Rapid advances in machine learning in recent years have begun to lower the technical hurdles to implementing AI, and various companies have begun to actively use machine learning. The accuracy of machine learning models is highly dependent on the quality of the training data.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. Because statistics: Last is the inherently probabilistic nature of ML.

Risk 359

Risk Modeling Data Processing Software 359

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. We’ll actually do this later in this article. These support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling. Modeling in R and Python.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Predictive models indicate that the machine learning market will grow at a compound annual growth rate (CAGR) of 38.8%

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Sisense

SEPTEMBER 25, 2020

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. Statistics and programming go hand in hand. Mastering statistical techniques and knowing how to implement them via a programming language are essential building blocks for advanced analytics. Linear regression.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Predictive models indicate that the machine learning market will grow at a compound annual growth rate (CAGR) of 38.8%

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

Smarten

APRIL 19, 2024

In this article, we will discuss the current state of AI in analytics, as well as the future of this burgeoning industry and how it can be applied to analytics to simplify and clarify results and to make analytics easier for businesses and business users to leverage.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

O'Reilly on Data

MARCH 23, 2021

On top of this, pre-existing societal biases are being reinforced and promulgated at previously unheard of scales as we increasingly integrate machine learning models into our daily lives. Put simply, we are reduced to the inputs of an algorithm.

Internet Publishing and Broadcasting 317

Internet Publishing and Broadcasting Broadcasting Data-driven Interactive 317

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Your Chance: Want to extract the maximum potential out of your data?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Data Science and Beyond

JULY 22, 2018

Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. This article is a short summary of my understanding of the definition of data science in 2018. It’s not all about machine learning. But what does it mean?

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. Let’s also look at the basic descriptive statistics for all attributes. It can be implemented as either unsupervised (e.g.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Domino Data Lab

OCTOBER 23, 2019

This article provides insight on the mindset, approach, and tools to consider when solving a real-world ML problem. As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. 05) in predicting changes in attendance. A complementary Domino project is available. Introduction.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

JULY 9, 2019

Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way. I still believe that data science is the craft of trying to apply machine learning to some real world problem.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Domino Data Lab

AUGUST 20, 2019

Many thanks to AWP Pearson for the permission to excerpt “Manual Feature Engineering: Manipulating Data for Fun and Profit” from the book, Machine Learning with Python for Everyone by Mark E. Missing values can be filled in based on expert knowledge, heuristics, or by some machine learning techniques.

Testing 68

Testing Modeling Interactive Measurement 68

Domino Data Lab

AUGUST 22, 2019

Note These three particular words are called articles , or determiners. Although it’s not perfect, [Note: These are statistical approximations, of course!] With the SG architecture, context words are predicted given the target word. With CBOW, it is the inverse: The target word is predicted based on the context words.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

datapine

NOVEMBER 27, 2019

We detailed the benefits and costs of good or bad quality data in our previous article on data quality management , where you can read the five important pillars to follow. However, businesses today want to go further and predictive analytics is another trend to be closely monitored.

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. The commercial use of predictive analytics is a relatively new thing.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Smarten

DECEMBER 3, 2023

This article will help you gather information about the topic of augmented analytics. 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.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Smarten

JUNE 21, 2018

This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. Time series forecasting methods are used to extract and analyze data and statistics and characterize results to more accurately predict the future based on historical data.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40

Jet Global

MAY 1, 2023

Advanced Analytics Some apps provide a unique value proposition through the development of advanced (and often proprietary) statistical models. Advanced Analytics Provide the unique benefit of advanced (and often proprietary) statistical models in your app. They can then pinpoint areas for improvement.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52