Data Science and Beyond

SEPTEMBER 19, 2016

Some people equate predictive modelling with data science, thinking that mastering various machine learning techniques is the key that unlocks the mysteries of the field. However, there is much more to data science than the What and How of predictive modelling. Stakeholders and their motives.

Data Science 66

Data Science Predictive Modeling Experimentation Deep Learning 66

CIO Business Intelligence

JUNE 7, 2022

Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning. Prescriptive analytics is a type of advanced analytics that involves the application of testing and other techniques to recommend specific solutions that will deliver desired outcomes.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Smarten

MAY 29, 2023

World-renowned technology analysis firm Gartner defines the role this way, ‘A citizen data scientist is 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. ‘If Advanced data preparation.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Business Objectives 52

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.’ Hypothesis Testing. Access to Flexible, Intuitive Predictive Modeling. Trends and Patterns. Forecasting.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Cloudera

OCTOBER 14, 2020

Lufthansa Technik extended a standard practice of placing sensors on aircraft engines and enabling predictive maintenance to automate fulfilment solutions. Step 1: Using the training data to create a model/classifier. This data will be used to train the model that can predict how many flights a given engine has until failure.

Machine Learning 97

Machine Learning Modeling Cost-Benefit Testing 97

Cloudera

MARCH 21, 2022

Data Science tools, algorithms, and practices are rapidly evolving to solve business problems on an unprecedented scale. This makes data science one of the most exciting fields to be in. There are well-known barriers that slow down predictive modeling or application development. Next Steps.

Machine Learning 79

Machine Learning Predictive Modeling Data Science Testing 79

DataRobot

MAY 25, 2021

DataRobot is excited to be awarded the 2021 ACT-IAC Innovation Award for ContagionNET, our pioneering rapid antigen test for COVID-19 that is at the forefront of pandemic preparedness and response. At the beginning of the pandemic, DataRobot committed to fighting against COVID-19 from a data science perspective.

Testing 52

Testing Predictive Modeling Data-driven Reporting 52

Smarten

APRIL 12, 2023

About Smarten The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Snapshot 52

Snapshot Key Performance Indicator KPI Business Intelligence 52

O'Reilly on Data

DECEMBER 12, 2019

Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Interpretable ML models and explainable ML.

Machine Learning 192

Machine Learning Modeling Testing Risk Management 192

Smarten

JUNE 17, 2022

After completion of the testing procedure, the certificate is provided to show that all requirements were met. The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

Domino Data Lab

OCTOBER 7, 2020

Statistical methods for analyzing this two-dimensional data exist. MANOVA, for example, can test if the heights and weights in boys and girls is different. This statistical test is correct because the data are (presumably) bivariate normal. The accuracy of any predictive model approaches 100%.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

Birst BI

AUGUST 23, 2018

What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases? Automating data science tasks leaves room to build more AI applications with the same amount of data science resources. Develop and test a model in R Studio.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Smarten

AUGUST 21, 2019

Smart Data Visualization – Smart Data Visualization gives users a helping hand with suggestions and recommendations for the best possible visualization of underlying data to generate meaningful insights from data.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

Business Over Broadway

SEPTEMBER 27, 2018

In our world of Big Data, marketers no longer need to simply rely on their gut instincts to make marketing decisions. Through the application of data science principles, marketing professionals now have a way of making evidence-based decisions to improve their marketing activities. genetic counseling, genetic testing).

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

DataRobot Blog

JUNE 23, 2022

Most successful ML and AI projects are replacing an existing prediction with a more accurate and/or faster one. Human intuition is relied on, or an older, hand-build BI/predictive model exists, or perhaps a set of heuristics were documented that more or less predict something. Automate and Scale Your Decisions.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

O'Reilly on Data

MAY 18, 2020

All predictive models are wrong at times?—just As the renowned statistician George Box once quipped , “All models are wrong, but some are useful.” Broadly speaking, materiality is the product of the impact of a model error times the probability of that error occuring. just hopefully less so than humans.

Risk 359

Risk Modeling Data Processing Software 359

CIO Business Intelligence

OCTOBER 13, 2023

Data scientist As companies embrace gen AI, they need data scientists to help drive better insights from customer and business data using analytics and AI. For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

Smarten

NOVEMBER 8, 2022

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Business Intelligence 52

Business Intelligence Predictive Modeling Statistics Data-driven 52

Juice Analytics

MARCH 11, 2021

How are you going to turn that data into a solution? There are many paths to consider: Visual representations that reveal patterns in the data and make it more human readable. Predictive models to take descriptive data and attempt to tell the future. He also tests data accuracy and product functionality.

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

DataRobot Blog

JUNE 3, 2022

Generative Pre-trained Transformer 3 (GPT-3) is a language model that utilizes deep-structured learning to predict human-like text. GPT-3 was created by OpenAI – a San Francisco-based artificial intelligence research laboratory – as the third-generation language prediction model in the GPT-n series. Download now.

Risk 52

Risk Predictive Modeling Modeling Technology 52

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

Birst BI

MAY 29, 2018

Today, BI vendors are already introducing AI capabilities in their products for data preparation, data discovery, and data science. For example, a false positive or false negative for cancer diagnosis can result in tremendous emotional distress, additional unnecessary tests, and even death.

Slice and Dice 74

Slice and Dice Analytics Business Intelligence Machine Learning 74

Insight

AUGUST 5, 2020

This created a summary features matrix of 7472 recordings x 176 summary features, which was used for training emotion label prediction models. Prediction models An Exploratory Data Analysis showed improved performance was dependent on gender and emotion. up to 20% for prediction of ‘happy’ in females?

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

O'Reilly on Data

SEPTEMBER 19, 2023

While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” You can see a simulation as a temporary, synthetic environment in which to test an idea. And it was good.

Machine Learning 249

Machine Learning Testing Modeling Cost-Benefit 249

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. A single model may also not shed light on the uncertainty range we actually face. Our team does a lot of forecasting.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Smarten

JANUARY 27, 2023

Smarten has announced the launch of Predictive Model Mark-Up Language (PMML) Integration capability for its Smarten Augmented Analytics suite of products. Simply create the predictive model, using your favorite platform, export the model as a PMML file and import that model to Smarten.

Predictive Modeling 52

Predictive Modeling Analytics Predictive Analytics Business Intelligence 52

Domino Data Lab

NOVEMBER 17, 2020

Our previous Domino Blog on the Curse of Dimensionality [2] , describes weird behaviors that emerge in data when P >> N: Points move far away from each other. Points fall on the outer edges of the data distribution. Predictive models fit to noise approach 100% accuracy. The 12 are listed in Table 1. Antimicrobial.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

DataRobot Blog

JANUARY 10, 2023

ML model builders spend a ton of time running multiple experiments in a data science notebook environment before moving the well-tested and robust models from those experiments to a secure, production-grade environment for general consumption. Deep Dive into DataRobot Notebooks. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Domino Data Lab

JULY 9, 2019

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins also indicated that data science, data engineering, and data analysis are different groups at The New York Times. Session Summary. Transcript. Feel free to email me.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Domino Data Lab

APRIL 21, 2021

This is to prevent any information leakage into our test set. 2f%% of the test set." 2f%% of the test set." Fraudulent transactions are 0.17% of the test set. 2f%% of the test set." Fraudulent transactions are 50.00% of the test set. Model training. Feature Engineering. References. [1]

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Alation

APRIL 14, 2022

A useful feature for exposing patterns in the data. Supports the ability to interact with the actual data and perform analysis on it. Automatic sampling to test transformation. Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Visual Profiling. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Sisense

SEPTEMBER 25, 2020

Linear regression is a form of supervised learning (or predictive modeling). In supervised learning, the dependent variable is predicted from the combination of independent variables. When a single independent variable is used to predict the value of a dependent variable, it’s called simple linear regression. Clustering.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

CIO Business Intelligence

MARCH 22, 2023

Additionally, federated learning does not address the inference stage, which still exposes data to the ML model during cloud or edge device deployment. Differential privacy Differential privacy provides margins on how much a single data record from a training dataset contributes to a machine-learning model.

Machine Learning 105

Machine Learning Cost-Benefit Modeling Risk 105

DataRobot Blog

DECEMBER 15, 2022

Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning. The order of the models will be based on the project’s metric—and can be changed based on your configuration.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. I held out 20% of this as a test set and used the remainder for training and validation.

Risk 67

Risk ROI Modeling Metrics 67

CIO Business Intelligence

AUGUST 15, 2023

Whether a project aims to improve suicide prevention using data science or to create new revenue streams by reimagining an organization’s core business, CIO 100 Award winners demonstrate the innovative spirit of today’s IT in the face of rapidly evolving organizational challenges. They turned to artificial intelligence to help.

IT 98

IT Manufacturing IoT Cost-Benefit 98