Cloudera

SEPTEMBER 20, 2022

A “comic book” in this context is a story told visually through a series of images, and optionally (though often) in conjunction with written language, e.g., in speech bubbles or as captions. Deep learning models are data hungry, and state-of-the-art systems like DALL·E 2 are trained with massive data sets of images scraped from the internet.

Deep Learning 87

Deep Learning Cost-Benefit Risk Data-driven 87

Domino Data Lab

SEPTEMBER 18, 2019

Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. Interactive Data Visualization in Python. There are a couple of commonly used interactive data visualization libraries in Python: Plotly and Bokeh. Introduction.

Visualization 99

Visualization Interactive Machine Learning Data Science 99

datapine

APRIL 15, 2020

It’s necessary to say that these processes are recurrent and require continuous evolution of reports, online data visualization , dashboards, and new functionalities to adapt current processes and develop new ones. The term “agile” was originally conceived in 2011 as a software development methodology.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Cloudera

SEPTEMBER 29, 2022

Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. This data model is also the structure of the contract that is defined between the producers and consumers of the data. Consumers subscribe to data products that are produced by the data producers.

Data Architecture 74

Data Architecture Metadata Data Warehouse Sales 74

AWS Big Data

APRIL 5, 2023

Showpad migrated over 70 dashboards with over 1,000 visuals. The serverless model was also compelling because we did not have to pay for server instances nor license fees per reader. Because QuickSight is serverless and uses a session-based pricing model, Showpad expects to see cost savings. With QuickSight, we pay for usage.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Domino Data Lab

SEPTEMBER 25, 2019

One of the most common ways of fitting time series models is to use either autoregressive (AR), moving average (MA) or both (ARMA). These models are well represented in R and are fairly easy to work with. AR models can be thought of as linear regressions of the current value of the time series against previous values.

Forecasting 87

Forecasting Modeling Statistics Optimization 87

datapine

AUGUST 29, 2022

He founded the project Apache Storm in 2011, which turned to be “one of the world’s most popular stream processors and has been adopted by many of the world’s largest companies, including Yahoo!, To start a more in-depth grasp of your own data sets, you can try our online data visualization tool for free with a 14-day trial !

Big Data 263

Big Data Data Analytics Analytics Data mining 263

AWS Big Data

MAY 4, 2023

After deployment, the user will have access to a Jupyter notebook, where they can interact with two datasets from ASDI on AWS: Coupled Model Intercomparison Project 6 (CMIP6) and ECMWF ERA5 Reanalysis. Dataset Variables Disk Size Xarray Dataset Size Region ERA5 2011–2020 (120 netcdf files) 53.5GB 364.1

Data Processing 96

Data Processing Metadata Informatics Interactive 96

Smart Data Collective

APRIL 2, 2019

According to Forbes in 2011, the idea of the Data Lake was already gaining traction as companies started to consider the idea of moving their data from off-site repositories to cloud-accessible online storage , a reality that was further cemented by the cheap availability of cloud storage. The Thrust for Data Lake Creation.

Data Lake 83

Data Lake Big Data OLAP Testing 83

Domino Data Lab

OCTOBER 9, 2019

The broom package is a great general purpose tool for converting R objects, such as lm models and kmeans clusterings, into nice, rectangular data.frames. > The result is visualized as a dendrogram in Figure 25.8. Aggregates", ] > # get rid of countries where all the indicators are NA > wbInfo <- wbInfo[which(rowSums(!

Statistics 100

Statistics Machine Learning Metrics Measurement 100

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

BizAcuity

MAY 10, 2022

Amazon strategically went with the pricing model of ‘on-demand’, allowing developers to pay only as-per their computational needs. 2011: IBM enters the cloud market with IBM SmartCloud. Microsoft also releases Power BI, a data visualization and business intelligence tool. EC2 was a more evolved version of a Virtual Machine.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. This post describes the bsts software package, which makes it easy to fit some fairly sophisticated time series models with just a few lines of R code. by STEVEN L. Forecasting (e.g.

Forecasting 64

Forecasting Statistics Modeling Software 64

Domino Data Lab

MARCH 3, 2019

What’s been the impact of using ML models on culture and organization? Who builds their models? We also used maturity , in other words how long had an enterprise organization been deploying ML models in production? “Three surveys of AI adoption reveal key advice from more mature practices”. Management.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

APRIL 3, 2019

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. As the story goes, the general history of DG is punctuated by four eras: “Application Era” (1960–1990) – some data modeling, ?though There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Occam's Razor

APRIL 25, 2011

The issues of course include people and jaded mental models and bureaucracy and a lack of time and the missing desire to be great and org structures, and bosses. " I'd postulated this rule in 2005, it is even more true in 2011. Doing anything on the web without a Web Analytics Measurement Model. Yet there they are.

Marketing 126

Marketing Measurement Metrics Testing 126

Domino Data Lab

JANUARY 6, 2019

Also, clearly there’s no “one size fits all” educational model for data science. Laura Noren, who runs the Data Science Community Newsletter , presented her NYU postdoc research at JuptyerCon 2018, comparing infrastructure models for data science in research and education. The Berkeley model addresses large university needs in the US.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

IBM Big Data Hub

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. For example, Apple made Siri a feature of its iOS in 2011.

Machine Learning 70

Machine Learning Deep Learning Interactive Modeling 70

Alation

FEBRUARY 20, 2020

She’s seen the evolution of the self-service analytics market from decision systems to business intelligence to data visualization to data science and automated intelligence. Another telltale sign of category creation is that it comes with a distinctive business model and profit model.” [7]. Subscribe to Alation's Blog.

Machine Learning 52

Machine Learning Marketing Reporting ROI 52