datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. The online program includes an additional nonrefundable technology fee of US$395 per course.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Data Science 101

JUNE 10, 2019

Getting your first data science job might be challenging, but it’s possible to achieve this goal with the right resources. Before jumping into a data science career , there are a few questions you should be able to answer: How do you break into the profession? What skills do you need to become a data scientist?

Data Science 96

Data Science Statistics Predictive Modeling Machine Learning 96

Smarten

NOVEMBER 23, 2023

“These tools enable data literacy and digital transformation and increase team productivity and creativity, encouraging power users and those with average technology skills to dive into analytics ad use fact-based decision-making to improve market positioning.”

Publishing 62

Publishing Marketing Analytics Predictive Modeling 62

Smarten

MARCH 18, 2019

Data Science and Predictive Analytics Made Simple! Imagine a world where data science and predictive analytics tools are created for business users!

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Predictive Analytics Visualization Software Analytics 40

Smarten

APRIL 25, 2024

Whether you are trying to solve a business problem, get to the heart of that problem, find a business opportunity, predict the need for resources, new products or locations or understanding changes in your customer buying behavior, you don’t have time to learn complex tools or take training in analytics.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

CIO Business Intelligence

JUNE 7, 2022

Data analytics and data science are closely related. Data analytics is a component of data science, used to understand what an organization’s data looks like. Generally, the output of data analytics are reports and visualizations. Data analytics vs. data analysis.

Data Analytics 133

Data Analytics Diagnostic Analytics Management Analytics 133

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.’ Access to Flexible, Intuitive Predictive Modeling. Apply Data Filters. Forecasting. Classification.

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Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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Predictive Analytics Analytics Predictive Modeling Data mining 121

Sisense

APRIL 10, 2020

One of the most-asked questions from aspiring data scientists is: “What is the best language for data science? People looking into data science languages are usually confused about which language they should learn first: R or Python. NLP can be used on written text or speech data. R or Python?”.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smarten

AUGUST 21, 2019

These tools allow business users to leverage augmented analytics that provide guides and suggestions to help the business user more quickly and effectively produce clear advanced analytics with little to no training, thereby transforming the average business user into a Citizen Data Scientist.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

DataRobot

NOVEMBER 1, 2021

Practitioners in the AI space are focused on the speed and accuracy of model predictions. But the end game for the applicability of models is not in the predictions, but the decisions they enable, and predictive models alone don’t ensure better decisions.

Machine Learning 98

Machine Learning Manufacturing Predictive Modeling Optimization 98

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

Smarten

SEPTEMBER 11, 2017

Read a report, attend a conference and your head is swirling with terms like ‘assisted predictive modeling’, plug n’ play predictive analysis, smart visualization, augmented data discovery and augmented data preparation. Take plug n’ play predictive analytics for example.

Predictive Modeling 61

Predictive Modeling Analytics Predictive Analytics Forecasting 61

DataRobot

JANUARY 13, 2022

But they often don’t have enough data scientists with the full range of domain expertise to realize its full value. Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise. DataRobot is just such a platform.

ROI 52

ROI Machine Learning Experimentation Data Science 52

Juice Analytics

MARCH 11, 2021

However, the data was essentially stored in old copies of the paper magazine, not a format that was conducive to delivering insights to their target audience. (3) People don’t want data, they want solutions. How are you going to turn that data into a solution? She crafts the interface and interactions to make the data intuitive.

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Predictive Modeling Visualization Reporting Interactive 128

Smarten

FEBRUARY 17, 2022

Without understanding the shift in workflow, responsibilities and how the use of data will change the enterprise, it is unlikely that the business will succeed in its Citizen Data Scientist initiative.

Predictive Modeling 76

Predictive Modeling Digital Transformation Enterprise Data Science 76

Smarten

JUNE 17, 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.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

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

Smarten

FEBRUARY 7, 2019

The Gartner report entitled, ‘Augmented Analytics Is the Future of Data and Analytics, published on October 31, 2018, includes the following strategic assumptions: By 2025, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.

Optimization 40

Optimization Analytics Predictive Modeling Data-driven 40

Sisense

SEPTEMBER 9, 2019

We were most interested in exploring if it was possible to predict the return rate on a new product based on historical return rates of products with similar features. Then we ran Kraken’s machine learning and predictive modeling engine to get the results. Full circle data experience: achieved. Lessons Learned.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

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

O'Reilly on Data

DECEMBER 12, 2019

If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. Small residuals usually mean a model is right, and large residuals usually mean a model is wrong. Interpretable ML models and explainable ML.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

Birst BI

AUGUST 23, 2018

Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases?

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Cloudera

JULY 18, 2018

To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities. Additionally, organizations are increasingly restrained due to budgetary constraints and having limited data sciences resources.

Machine Learning 50

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 50

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs.

Data mining 58

Data mining Machine Learning Deep Learning Marketing 58

AWS Big Data

MARCH 7, 2023

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. Popular consumption entities in many organizations are queries, reports, and data science workloads.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

Birst BI

MAY 29, 2018

Today, BI vendors are already introducing AI capabilities in their products for data preparation, data discovery, and data science. Figure 6: Amazon Machine Learning to build and deploy Predictive Models. Therefore, this synergy makes the BI industry a prime candidate to use and apply AI successfully.

Slice and Dice 74

Slice and Dice Analytics Business Intelligence Machine Learning 74

Smarten

DECEMBER 3, 2023

Adopting Augmented Analytics: How to Get Started Gartner has predicted that, in the future ‘…40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’

Analytics 40

Analytics Data Warehouse Metrics Interactive 40

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. imputation of missing values). ref: [link].

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

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

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

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. Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning?

Machine Learning 82

Machine Learning Modeling Deep Learning Predictive Modeling 82

Domino Data Lab

AUGUST 12, 2021

For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with. In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

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