Smart Data Collective

JUNE 4, 2021

What is data science? Data science is analyzing and predicting data, It is an emerging field. Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. These data models predict outcomes of new data. Statistics.

Data Science 104

Data Science Statistics Deep Learning Machine Learning 104

CIO Business Intelligence

MAY 5, 2022

The boom in data science continues unabated. The work of gathering and analyzing data was once just for a few scientists back in the lab. Now every enterprise wants to use the power of data science to streamline their organizations and make customers happy. Data scientists use them to swap ideas and deliver ideas.

Data Science 130

Data Science Analytics Machine Learning Optimization 130

DataRobot Blog

JULY 28, 2022

This article presents a case study of how DataRobot was able to achieve high accuracy and low cost by actually using techniques learned through Data Science Competitions in the process of solving a DataRobot customer’s problem. Sensor Data Analysis Examples. The Best Way to Achieve Both Accuracy and Cost Control.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Analytics Vidhya

APRIL 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction What is the first measure coming into your mind. The post Confusion Matrix: Detailed intuition and trick to learn appeared first on Analytics Vidhya.

Measurement 322

Measurement Data Science Publishing Analytics 322

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. 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.

Data Science 58

Data Science Machine Learning Cost-Benefit Deep Learning 58

Data Science and Beyond

JANUARY 11, 2020

I learned about Bayesian statistics and conjugate priors. Back then, it seemed like “real” data science consisted of building and tuning machine learning models – that’s what Kaggle was all about. In reality, problem definition and solution measurement are more challenging and important.

Software 103

Software Data Science Machine Learning Deep Learning 103

CIO Business Intelligence

JUNE 7, 2022

It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. It is frequently used for risk analysis.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

CIO Business Intelligence

JUNE 14, 2023

Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications. The number of data analytics certs is expanding rapidly.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Rocket-Powered Data Science

MARCH 19, 2021

Focus on the strategies that aim these tools, talents, and technologies on reaching business mission and goals: e.g., data strategy, analytics strategy, observability strategy ( i.e., why and where are we deploying the data-streaming sensors, and what outcomes should they achieve?).

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

Analytics Vidhya

MAY 2, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. “Skewness essentially measures the symmetry of the distribution, while kurtosis. The post Shape of data: Skewness and Kurtosis appeared first on Analytics Vidhya.

Measurement 175

Measurement Data Science Publishing Analytics 175

Smarten

APRIL 25, 2024

Users can harness the power of statistics and machine learning to uncover hidden insights and improve the overall quality of your data. Data insights provide actionable recommendations to address various types of data quality errors, enabling users to take prompt corrective actions for improved data integrity.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

CIO Business Intelligence

JANUARY 17, 2024

To do this, Ipsos uses large language models to generate cutting-edge insights built using AI capabilities, complemented by its data science models and tailored to the services it offers,” says Mohammed. According to Mohammed, the results of this digital transformation journey are measurable and impressive. js and React.js.

Digital Transformation 119

Digital Transformation Dashboards Reporting Data Science 119

bridgei2i

JANUARY 25, 2022

The Basic Guide to Data Science at the Workplace. The Basic Guide to Data Science at the Workplace. In this podcast episode, AI enthusiasts Anirudh and Janci talk about how sincere curiosity and passion for learning can help anyone understand data science and become an active contributor. Subscribe Now.

Data Science 52

Data Science Machine Learning Data-driven Statistics 52

Business Over Broadway

SEPTEMBER 5, 2018

The devastating impact of natural disasters can be measured in human suffering, loss of life and economic impact. Even though natural events such as floods, earthquakes or hurricanes are inevitable, I believe that their impact can be mitigated through the application of data and analytics. Data is the Fuel; Data Science is the Engine.

Data Science 57

Data Science Statistics Advertising Deep Learning 57

Rocket-Powered Data Science

JULY 7, 2019

Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics). Algorithm: A set of rules to follow to solve a problem or to decide on a particular action (e.g., They provide more like an FAQ (Frequently Asked Questions) type of an interaction. Industry 4.0 4) Prosthetics.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

DataRobot Blog

SEPTEMBER 1, 2022

These and many other questions are now on top of the agenda of every data science team. To quantify how well your models are doing, DataRobot provides you with a comprehensive set of data science metrics — from the standards (Log Loss, RMSE) to the more specific (SMAPE, Tweedie Deviance).

Metrics 145

Metrics Statistics Modeling Data Science 145

O'Reilly on Data

NOVEMBER 13, 2018

Data Platforms. Over the last 12-18 months, companies that use a lot of ML and employ teams of data scientists have been describing their internal data science platforms (see, for example, Uber , Netflix , Twitter , and Facebook ). Classification parity means that one or more of the standard performance measures (e.g.,

Machine Learning 220

Machine Learning Risk Management Statistics 220

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. A background in (or a firm grasp of) data warehousing and mining. BI engineer.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

IBM Big Data Hub

NOVEMBER 29, 2023

For instance, if a business prioritizes accuracy in generating synthetic data, the resulting output may inadvertently include too many personally identifiable attributes, thereby increasing the company’s privacy risk exposure unknowingly. Synthetic data provides a faster alternative for training machine learning models.

Metrics 88

Metrics Machine Learning Risk Statistics 88

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

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Business Objectives 52

Smart Data Collective

SEPTEMBER 19, 2022

Statistics show that 93% of customers will offer repeat business when they encounter a positive customer experience. To ensure their customers have a satisfactory experience, financial businesses will use big data analytics to tweak their services across various platforms to suit a customer’s needs.

Big Data 129

Big Data ROI Measurement Risk 129

Domino Data Lab

OCTOBER 7, 2020

This could be lots of rows (samples) and few columns (variables) like credit card transaction data, or lots of columns (variables) and few rows (samples) like genomic sequencing in life sciences research. Each variable in a data set is a dimension with the set of variables defining the space in which the samples fall.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

Smart Data Collective

OCTOBER 17, 2022

Email marketing is the most acceptable way to give precise customer data, but you must guarantee your efforts aren’t wasted. Using data analytics help your email marketing strategies succeed. Data Analytics’ Importance in Email Marketing. Like any other marketing strategy, you must measure email performance.

Marketing 119

Marketing Optimization Data Analytics Analytics 119

Data Science 101

JANUARY 15, 2020

Reliability: It means measurements should have repeatable results. For eg: you measure the blood pressure of a person. Then after some time, you take the measurement again and there is a huge fluctuation in the result. So instruments should be checked well before taking measurements. Statistics Essential for Dummies by D.

Experimentation 96

Experimentation Statistics Measurement Testing 96

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Error detection and automatic repairing/imputation.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

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

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Smart Data Collective

NOVEMBER 26, 2021

With the “big data” or insurmountable, high-volume amount of information, data analytics plays a crucial role in many business aspects, including revenue marketing. Data analytics refers to the systematic computational analysis of statistics or data. It lays a core foundation necessary for business planning.

Marketing 110

Marketing Data Analytics Key Performance Indicator Analytics 110

CIO Business Intelligence

SEPTEMBER 2, 2022

This uniquely skilled, relatively new breed of data experts gathers and analyzes data — both structured and unstructured — to solve real business problems, using statistics, machine learning, algorithms, and natural language processing. We, like many other institutions, are seeing a very large growth in our amount of data.

Manufacturing 98

Manufacturing Data Science Machine Learning Reporting 98

CIO Business Intelligence

SEPTEMBER 1, 2022

This uniquely skilled, relatively new breed of data experts gathers and analyzes data — both structured and unstructured — to solve real business problems, using statistics, machine learning, algorithms, and natural language processing. We, like many other institutions, are seeing a very large growth in our amount of data.

Manufacturing 98

Manufacturing Data Science Machine Learning Reporting 98

O'Reilly on Data

MAY 18, 2020

And last is the probabilistic nature of statistics and machine learning (ML). Most AI models decay overtime: This phenomenon, known more widely as model decay , refers to the declining quality of AI system results over time, as patterns in new data drift away from patterns learned in training data.

Risk 359

Risk Modeling Data Processing Software 359

O'Reilly on Data

JULY 28, 2020

There’s a substantial literature about ethics, data, and AI, so rather than repeat that discussion, we’ll leave you with a few resources. Ethics and Data Science is a short book that helps developers think through data problems, and includes a checklist that team members should revisit throughout the process.

Marketing 362

Marketing Experimentation Metrics Testing 362

Smarten

JUNE 17, 2022

.” The Information Technology Amendment Act of 2009 designated CERT-IN as the national agency to perform functions for cyber security, including the collection, analysis and dissemination of information on cyber incidents, as well as taking emergency measures to handle incidents and coordinating cyber incident response activities.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

Jen Stirrup

JUNE 16, 2020

Convincing Your HiPPo: Business Statistics for AI and Data Science ( Wednesday 15th July at 12.30pm EST, 5.30pm BST ). To be successful and confident for working AI and Data Science, it’s important to have a grasp of statistics. How can you tell if your models are good?

Statistics 65

Statistics Visualization Machine Learning Business Intelligence 65

CIO Business Intelligence

APRIL 14, 2022

Low code and no code options are making it easier for anyone to click a few buttons and produce a report or download a spreadsheet loaded with data, all without setting up an endless series of meetings with the developers. The companies also emphasize their connections to good artificial intelligence algorithms and data science options.

Enterprise 138

Enterprise Marketing Measurement Reporting 138

Smart Data Collective

OCTOBER 7, 2023

Marco Cerliani has a great article in Towards Data Science on the benefits of AI in the people tracing field. Safety Measures: In many modern airports, facial recognition systems are deployed to verify passenger identities, ensuring faster and more secure processing.

Technology 92

Technology Snapshot Data-driven Machine Learning 92

Smart Data Collective

JULY 16, 2021

Big data analytics involves models that consist of data science and statistics that help companies find vulnerabilities. With big data becoming more prominent across organizations, implementing security analytics is the most efficient way to keep track of potential threats.

Analytics 129

Analytics Big Data Machine Learning Statistics 129