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 121

Big Data Data Analytics Analytics Predictive Modeling 121

Rocket-Powered Data Science

JULY 7, 2019

Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics). Chatbots cannot hold long, continuing human interaction. Traditionally they are text-based but audio and pictures can also be used for interaction. 5) Big Data Exploration. 4) Design. (5)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

AWS Big Data

JUNE 20, 2023

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) and data sources residing in AWS, on-premises, or other cloud systems using SQL or Python. You can create features using standard SQL on Athena without using any other service for feature engineering.

Data Lake 73

Data Lake Data Science Recreation/Entertainment Experimentation 73

DataRobot Blog

OCTOBER 18, 2022

As AI-driven use cases increase, the number of AI models deployed increases as well, leaving resource-strapped data science teams struggling to monitor and maintain this growing repository. “We These accelerators are specifically designed to help organizations accelerate from data to results. See DataRobot AI Cloud in Action.

Big Data 96

Big Data Forecasting Experimentation Metrics 96

Cloudera

AUGUST 20, 2020

Through its Enterprise AI and Data Science (EAI) and Digital Bank Engagement Labs (eLabs) UOB collabora ted to implement AI and data science solutions to understand customer behaviours and characteristics from transaction and interaction data. The organisation also wanted to ensure better customer s ervice.

Enterprise 121

Enterprise Experimentation Uncertainty Deep Learning 121

Cloudera

APRIL 9, 2021

To effectively leverage their predictive capabilities and maximize time-to-value these companies need an ML infrastructure that allows them to quickly move models from data pipelines, to experimentation and into the business. Finally, CML has built-in model security and governance thanks to Cloudera Shared Data Experience (SDX).

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

O'Reilly on Data

MARCH 19, 2020

Aggregating artificial intelligence and machine learning topics accounts for nearly 5% of all usage activity on the platform, a touch less than, and growing 50% faster than, the well-established “data science” topic (see Figure 2). The chatbot was one of the first applications of AI in experimental and production usage.

Deep Learning 274

Deep Learning Machine Learning Data-driven Modeling 274

CIO Business Intelligence

SEPTEMBER 27, 2023

By suggesting a number of use cases, we further encourage experimentation and creative application.” Fostering a culture of learning Skillsoft, a provider of education services and technology, has been leveraging AI for some time to deliver personalized, dynamic, and interactive learning experiences for users.

Strategy 116

Strategy Risk Data-driven Modeling 116

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

AUGUST 5, 2019

This Domino Data Science Field Note covers Chris Wiggins ‘s recent data ethics seminar at Berkeley. He also encouraged data scientists to understand how new data science algorithms rearrange power as well as how the history of data is a story of truth and power.

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

The Unofficial Google Data Science Blog

JANUARY 14, 2016

by AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science. We must therefore maintain statistical rigor in quantifying experimental uncertainty. In this post we explore how and why we can be “ data-rich but information-poor ”.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. Example: A student is struggling with a complex math concept.

Cost-Benefit 90

Cost-Benefit Modeling Manufacturing Interactive 90

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

accounting for effects "orthogonal" to the randomization used in experimentation. For example in ads, experiments using cookies (users) as experimental units are not suited to capture the impact of a treatment on advertisers or publishers nor their reaction to it. To see this, imagine you want to study long-term effects in an A/B test.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

The Unofficial Google Data Science Blog

APRIL 16, 2019

by MICHAEL FORTE Large-scale live experimentation is a big part of online product development. This means a small and growing product has to use experimentation differently and very carefully. This blog post is about experimentation in this regime. But these are not usually amenable to A/B experimentation.

Experimentation 68

Experimentation Sales Metrics Measurement 68

Insight

APRIL 28, 2020

Originally posted on Open Data Science (ODSC). In this article, we share some data-driven advice on how to get started on the right foot with an effective and appropriate screening process. Designing a Data Science Interview Onsite interviews are indispensable, but they are time-consuming.

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

DataRobot

SEPTEMBER 14, 2021

And for those that do make it past the experimental stage, it typically takes over 18 months for the value to be realized. This helps experts save time on mundane coding tasks so they can spend more time focusing on experimenting with data, advanced algorithms, and other high-value data science activities.

Machine Learning 94

Machine Learning Modeling Experimentation Visualization 94

Smart Data Collective

MAY 20, 2019

By 2020, over 40 percent of all data science tasks will be automated. Quantitative analysis, experimental analysis, data scaling, automation tools and, of course, general machine learning are all skills that modern data analysts should seek to hone. Machine Learning Experience is a Must.

Analytics 111

Analytics Machine Learning Business Intelligence Big Data 111

DataRobot

JUNE 23, 2021

As they strive to improve models, data scientists continually try new approaches to refine their predictions. To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. In data science , the best results come through experimentation. So let’s dig in! Run AutoPilot.

Machine Learning 52

Machine Learning Experimentation Visualization Modeling 52

DataRobot

APRIL 19, 2021

When the machine learning algorithm is trained, data scientists take the outputs (predictions), apply business rules to turn predictions into decisions, and send these predictions and decisions into the organization’s computer systems. They need data assembly, data science, integration, and visualization skills.

Machine Learning 52

Machine Learning Visualization Data-driven Data Science 52

Domino Data Lab

DECEMBER 4, 2020

This tutorial will show how easy it is to integrate and use Pumas in the Domino Data Science Platform , and we will carry out a simple non-compartmental analysis using a freely available dataset. The Domino data science platform empowers data scientists to develop and deliver models with open access to the tools they love.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. The approach they’ve used applies to other popular data science APIs such as NumPy , Tensorflow , and so on.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

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. Data Analysis Libraries.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

The Unofficial Google Data Science Blog

JANUARY 16, 2018

Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. However, this assumption no longer holds when samples interact with each other, such as in a network. This simulation is based on the actual user network of GCP.

Testing 58

Testing Experimentation Measurement Modeling 58

datapine

JANUARY 31, 2022

It’s all about using data to get a clearer understanding of reality so that your company can make more strategically sound decisions (instead of relying only on gut instinct or corporate inertia). Ultimately, business intelligence and analytics are about much more than the technology used to gather and analyze data.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

IBM Big Data Hub

SEPTEMBER 25, 2023

Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes. Uber chose Presto for the flexibility it provides with compute separated from data storage. What is Presto?

OLAP 87

OLAP Data Lake Data-driven Snapshot 87

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. back to the structure of the dataset. Let’s look through some antidotes. Ergo, less interpretable.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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. Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. They have the foundations of data infrastructure. Yet, this challenge is not insurmountable.

Management 110

Management Machine Learning Experimentation Metrics 110

The Unofficial Google Data Science Blog

MARCH 22, 2018

But what if users don't immediately uptake the new experimental version? Background At Google, experimentation is an invaluable tool for making decisions and inference about new products and features. Naturally, this issue is of particular concern to us in the Play Data Science team.

Experimentation 62

Experimentation Measurement Modeling Statistics 62

The Unofficial Google Data Science Blog

JULY 31, 2016

To figure this out, let's consider an appropriate experimental design. In other words, the teacher is our second kind of unit, the unit of experimentation. This type of experimental design is known as a group-randomized or cluster-randomized trial. The second source of dependence comes from student interactions.

Experimentation 42

Experimentation Testing Measurement Metrics 42

Alation

SEPTEMBER 28, 2022

This requires that data engineers embrace learning and integrating new technologies, such as AI tools. In DataOps, a variety of analytics & data science skills , qualifications , tools, and roles are required for increased innovation and a productive team. Daily Interactions. It’s a Team Sport. Self-Organize.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

bridgei2i

APRIL 28, 2020

And so that process with curation or identifying which data potentially is a leading indicator and then test those leading indicators. It takes a lot of data science, a lot of data curation, a lot of data integration that many companies are not prepared to shift to as quickly as the current crisis demands.

Enterprise 103

Enterprise Data Analytics Analytics Forecasting 103

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. This blog post introduces the notions of representational uncertainty and interventional uncertainty to paint a fuller picture of what the practicing data scientist is up against. Vignette: Data Science at fluff.ai

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

Our post describes how we arrived at recent changes to design principles for the Google search page, and thus highlights aspects of a data scientist’s role which involve practicing the scientific method. There has been debate as to whether the term “data science” is necessary. Some don’t see the point.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

Insight

MARCH 12, 2020

With breaking this bottleneck in mind, I’ve used my time as an Insight Data Science Fellow to build the AIgent, a web-based neural net to connect writers to representation. of users tagged Cuckoo’s Calling with ‘science-fiction’, but 10% of users tagged it with ‘mystery’, we should be more confident in the latter label.

Modeling 59

Modeling Metadata Publishing Sales 59

Domino Data Lab

AUGUST 26, 2019

Models are at the heart of of data science and increasing predictive accuracy of models is a core expectation upon industry. The project also covers building a pipeline for automating ML workflow and stay tuned for additional hyperparamater content on the Domino Data Science blog. In [1]: # setup.

Testing 79

Testing Modeling Machine Learning Metrics 79

Domino Data Lab

AUGUST 22, 2019

Data scientists and researchers require an extensive array of techniques, packages, and tools to accelerate core work flow tasks including prepping, processing, and analyzing data. Utilizing NLP helps researchers and data scientists complete core tasks faster. Interactive bokeh plot of two-dimensional word-vector data.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111