CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. Organization: Columbia University Price: Students pay Columbia Engineering’s rate of tuition (US$2,362 per credit).

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4) See [link].

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

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. Ultimately, the evaluation is based on whether or not the model delivers success to the customers’ business. Therefore, a value below 0.5

Data Science 72

Data Science Machine Learning Statistics Modeling 72

CIO Business Intelligence

MARCH 21, 2022

Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies. It doesn’t conform to a data model but does have associated metadata that can be used to group it.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Structured Data 137

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate. And sometimes even if it is not[1].)

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

DataRobot

JANUARY 13, 2022

Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise. It offers a visual and intuitive UI that enables anyone to explore and prepare data for machine learning, no matter their previous machine-learning experience.

ROI 52

ROI Machine Learning Experimentation Data Science 52

Business Over Broadway

MAY 22, 2019

According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT. Remember that digital transformation is about transforming your business and operating models with technology.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Domino Data Lab

JANUARY 24, 2019

These solutions help data analysts build models by automating tasks in data science, including training models, selecting algorithms, and creating features. These tools support a breadth of use cases including data science, data engineering, and model operations. Proprietary (often GUI-driven) data science platforms.

Data Science 65

Data Science Marketing Data-driven Statistics 65

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.

Cost-Benefit 93

Cost-Benefit Modeling Manufacturing Interactive 93

Occam's Razor

MARCH 23, 2021

A key part of how this manifested in our work was doing truly super-advanced machine-learning powered analysis to answer hard questions that few can successfully. We’ve chosen to use machine learning algorithms that learn from the underlying structures inside massive amounts of our datasets without explicit programming.

Analytics 131

Analytics Scorecard Strategy Testing 131

Insight

MARCH 12, 2020

The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Features: DistilBERT Text Embeddings Once I had a raw dataset, I could begin engineering features and building a natural language processing (NLP) model.

Modeling 59

Modeling Metadata Publishing Sales 59

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. You can use a regression model. A complementary Domino project is available. . Introduction.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

FineReport

DECEMBER 19, 2019

When it comes to data analysis, from database operations, data cleaning, data visualization , to machine learning, batch processing, script writing, model optimization, and deep learning, all these functions can be implemented with Python, and different libraries are provided for you to choose. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Ontotext

APRIL 3, 2024

W hen you try to automate business processes, semantics, and machine learning , knowledge graphs can bring a lot of value. Nimit Mehta: I think that 2024 is going to be a buckle-down year, but, at the same time, we’ll see a rapid explosion of experimentation. These are not statistical inferences. Maybe later.

Technology 59

Technology Risk Digital Transformation Measurement 59

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

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. Among these, only statistical uncertainty has formal recognition.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Domino Data Lab

DECEMBER 4, 2020

NCA doesn’t require the assumption of a specific compartmental model for either drug or metabolite; it is instead assumption-free and therefore easily automated [1]. PharmaceUtical Modeling And Simulation (or PUMAS) is a suite of tools to perform quantitative analytics for pharmaceutical drug development [2]. Mean residence time.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Occam's Razor

JULY 24, 2018

work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more. The Implications of Complexity.

Analytics 93

Analytics Metrics Strategy Measurement 93

Paul DeBeasi

JANUARY 30, 2019

Machine learning projects are inherently different from traditional IT projects in that they are significantly more heuristic and experimental, requiring skills spanning multiple domains, including statistical analysis, data analysis and application development. Four Options for Integrating Machine Learning with IoT.

Machine Learning 56

Machine Learning IoT Experimentation Statistics 56

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

JUNE 4, 2018

I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Not easy, but your business model has to change to survive.). Mercifully, Machine Learning (/Artificial Intelligence) will help us solve this challenge with incredible results.

Strategy 124

Strategy Cost-Benefit Testing Sales 124

Business Over Broadway

FEBRUARY 21, 2021

As such, data science requires three broad skill sets , including subject matter expertise, statistics/math and technology/programming. Kaggle conducted a worldwide survey of over 20000 data professionals to learn about the state of data science and machine learning. What broad activities make up their respective jobs?

Machine Learning 60

Machine Learning Statistics Data Science Experimentation 60

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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. It’s not all about machine learning. It is now much easier to deploy machine learning models, even without a deep understanding of how they work.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

Corinium

APRIL 25, 2019

For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. This is a much more proactive and scalable model. And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. In the present chapter [excerpt], we cover code that will enable you to create your own word vectors as well as to provide them as an input into a deep learning model. A complementary Domino project is available.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Domino Data Lab

AUGUST 26, 2019

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. Data scientists, machine learning (ML) researchers, and business stakeholders have a high-stakes investment in the predictive accuracy of models. Introduction.

Testing 79

Testing Modeling Machine Learning Metrics 79

Cloudera

NOVEMBER 25, 2020

How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? And most importantly, once shared security model across data sets and compute accessing the data. It would enable faster experimentation with easy, protected, and governed access to a variety of data.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation. Note also that this account does not involve ambiguity due to statistical uncertainty. We sliced and diced the experimental data in many many ways.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45