FineReport

JANUARY 5, 2020

The bar chart below shows the sales of each category of products, and the line chart above shows the annual sales of a certain category of products. In the upper right corner of the dashboard is a word cloud diagram showing the categories of Christmas gifts people most want. We can also customize the style of the flow lines.

Dashboards 95

Dashboards Sales Visualization Reporting 95

O'Reilly on Data

JANUARY 25, 2021

All too often, trends degenerate into horse races over languages and platforms. Look at all the angst heating up social media when TIOBE or RedMonk releases their reports on language rankings. Those reports are valuable, but their value isn’t in knowing what languages are popular in any given month. Programming Languages.

Machine Learning 363

Machine Learning Software Testing Technology 363

The Data Visualisation Catalogue

JANUARY 24, 2023

For those unaware, ChatGPT is a large language model developed by OpenAI. Point #3 is kind of pointless or badly written because the category names should already be in the category axis. It uses a transformer-based neural network architecture and is trained on a gigantic dataset of human-generated text.

Visualization 107

Visualization Interactive Data-driven Testing 107

Data Science 101

MAY 20, 2019

There were a number of questions from this category. Python was the language of choice for the exam, so focus on it. R Power BI Publishing Azure ML models. Questions ranged from the basics of how to import data all the way to specifics about certain modules. Azure Products. Not on the exam.

Data Science 111

Data Science Machine Learning Deep Learning Testing 111

O'Reilly on Data

MARCH 18, 2020

The sample is far from tech-laden, however: the only other explicit technology category—“Computers, Electronics, & Hardware”—accounts for less than 7% of the sample. The “Other” category (~22%) comprises 12 separate industries. Think broadly: AI is used everywhere, not just in R&D and IT. Industry of survey respondents.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

Ontotext

MAY 2, 2024

We can talk about three categories, each with different sophistication, but all valuable in and of themselves. Like many other Pharma companies, they kept data on R&D, clinical trials, reporting, and post-clinical trials in disparate data hubs. Use case-driven growth How do we take data and create value?

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

O'Reilly on Data

SEPTEMBER 15, 2020

Teams with more experience with techniques such as natural language processing and computer vision are more likely to be successful building new applications using the same techniques. Outputs from trained AI models include numbers (continuous or discrete), categories or classes (e.g., characters, words, or sentences).

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

The Unofficial Google Data Science Blog

JULY 18, 2023

This type of data might appear when multiple psychiatrists make diagnoses on patients, or in studying various “leadership categories.” There are two possible categories for someone to select: Yes, contains guitar, and No, does not contain guitar. To answer the question “does this image contain a guitar?”

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Data Science 101

OCTOBER 17, 2023

I shift verbs, insert or remove what might seem Boolean to a machine understanding, try all natural language or all Boolean for the same end, grab all of the output, run a diff, take notes, compare, refine. It becomes a dance. The same happens in Midjourney, thus my daily work there. I’m not doing that work to get pretty things.

Consulting 59

Consulting Interactive Data-driven IT 59

Juice Analytics

DECEMBER 16, 2019

Rule #4: Tidy by category, not by location One of the most common mistakes people make is to tidy room by room. Get inspired by the people who create data stories. Tidying up means we only showcase the data that brings us direct, clear value — everything else should be discarded from our presentations.

Dashboards 67

Dashboards Metrics Visualization Interactive 67

FineReport

NOVEMBER 18, 2019

In FineReport, the chart’s workflow is similar to Excel, Data Preparation – Insert Chart – Select Chart Type – Select Category Axis, Series Name and Series Value – Set Chart Style. Basic Chart Production Process. Different charts. – Use Excel’s built-in charts to do some regular charts.

Visualization 81

Visualization Dashboards Reporting Sales 81

Jet Global

JULY 2, 2019

For example, Azure Data Lake includes all the capabilities required to make it easy for developers, data scientists, and analysts to store data of any size, shape, and speed—and do all types of processing and analytics across platforms and languages.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

CIO Business Intelligence

MAY 18, 2023

This sort of transformative revelation might seem like a lot to expect from paper and ink (or e-ink) but printed language is where humans — even those who are building cutting-edge digital technologies for a living — still store our best ideas. In the book, he examines robotics, AI, cybercrime, genomics, big data, and more. “It

IT 128

IT Software Recreation/Entertainment Technology 128

Domino Data Lab

AUGUST 29, 2019

R is the distribution of reward given a state-action pair—some particular state paired with some particular action—denoted as ( s, a ). It’s a distribution in the sense of being a probability distribution: The exact same state-action pair ( s, a ) might randomly result in different amounts of reward r on different occasions.

Optimization 111

Optimization Modeling Deep Learning Metrics 111

erwin

APRIL 4, 2022

“Because erwin Data Modeler and erwin Data Intelligence are closely aligned and provide complementary services, it just made sense to align the release naming convention,” said Prashant Parikh, vice president, Development Engineering, R&D at Quest Software. “So, What’s new in erwin Data Modeler R12.0? DevOps GitHub integration via Mart.

Modeling 52

Modeling Data Processing Data-driven Big Data 52

Insight

FEBRUARY 19, 2020

The starpower of each actor, in turn, is the sum of the average IMDb user ratings for the top-4 “known For” movies for that actor, according to IMDb (Images: R. The genre uniqueness is a measure of how unique a movie’s combination of genre categories is relative to all movies in my data set.

Risk 67

Risk ROI Modeling Metrics 67

Domino Data Lab

JULY 1, 2020

Recently there has been an influx of newcomers, and data scientists now have a wide range of implementations to choose from, such as Juptyer, Zeppelin, R Markdown, Spark Notebook, and Polynote. This section is written with Python in mind, but the principles outlined can also apply to other coding languages such as R.

Testing 116

Testing Data Science Machine Learning Data-driven 116

Grooper

AUGUST 19, 2019

Read on to learn how data literacy, information as a second language, and insight-driven analytics take digital strategy to a new level. C-level executives and professionals alike must learn to speak a new language - data. Data literacy is solved by a structured program of learning information as a second language (ISL).

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Insight

MAY 16, 2019

This involves classifying images into different categories by applying a distinctive type of multi-layer neural network called Convolutional Neural Networks (CNN). Image metadata such as properties and bounding box coordinates are saved as XML. Beyond Image Classification Image classification is a very popular problem in computer vision.

Deep Learning 84

Deep Learning Machine Learning Metadata Data Science 84

FineReport

JANUARY 5, 2022

Therefore, using R, Python, and other data analysis languages, referred to as the chart function package, present visual data and analysis. FR categorizes reports into three broad categories and creates functionality to meet various style requirements: general reports, aggregation reports, and decision reports.

Reporting 52

Reporting Analytics Visualization Dashboards 52

The Unofficial Google Data Science Blog

MARCH 13, 2017

For instance, they identify objects in images, perform language translation, enable web search — all with surprising accuracy. It takes an image as input and assigns scores for 1000 different ImageNet categories. The input is specified via the R,G,B values of the pixels of the image.

IT 68

IT Visualization Modeling Uncertainty 68

CIO Business Intelligence

OCTOBER 19, 2023

You can also prompt Power BI to suggest questions it can answer about a report, or you can describe in everyday language the insights you need and Power BI will provide visualizations in response. Smart Narratives pull out key takeaways and trends in your data and wrap them with autogenerated text to build data stories.

Slice and Dice 126

Slice and Dice Scorecard Metrics Visualization 126

Domino Data Lab

JULY 1, 2021

The categories that the named entities are classified into are predefined and often contain entries like locations, organisations, job types, personal names, times and others. Named Entity Recognition (NER) is an NLP problem, which involves locating and classifying named entities (people, places, organizations etc.) 260-270, [link] .

Modeling 111

Modeling Statistics Testing Metrics 111

Sisense

JUNE 26, 2020

As datasets become bigger and more complex, only AI, materialized views, and more sophisticated coding languages will be able to glean insights from them. Both Python and R are advanced coding languages that can produce beautiful images that allow humans to understand vast datasets with ease. Data Visualization in R.

Visualization 97

Visualization Unstructured Data Measurement Data-driven 97

The Unofficial Google Data Science Blog

MARCH 22, 2018

Before we begin, we should state our overall goal estimand, which is the expected effect of the treatment on the average single unit: $$ theta = E(Y|U=1) - E(Y|U=0) $$ In the language of counterfactuals, this gives the difference between the outcomes under the two different treatment conditions. References [1] Have, Thomas R.

Experimentation 62

Experimentation Measurement Modeling Statistics 62

Sisense

FEBRUARY 20, 2020

Analytics is constantly evolving; as datasets become bigger and more complex, only AI, materialized views, and more sophisticated coding languages will be able to glean insights from them. In these problems, we attempt to predict whether an object or an event belongs to a certain category.

Testing 93

Testing Modeling Machine Learning Visualization 93

Sisense

APRIL 13, 2020

Or perhaps instead they prefer to hone their skills in SQL , Python, or R. If data science is your jam, there are so many exciting new developments in AI, machine learning, natural language processing, and graph databases that you could keep busy reading for days on end.

Uncertainty 83

Uncertainty Marketing Digital Transformation Forecasting 83

Sisense

JUNE 6, 2019

And with the recent merger with Periscope Data, data teams can also work with common languages like SQL, Python, and R to bring better insights to analysts and end users. I am confident that Sisense Labs and the innovations coming from this team will put us over the top in this category in the coming years. out of 5.0)

Reporting 75

Reporting Business Intelligence Visualization Digital Transformation 75

Business Over Broadway

DECEMBER 20, 2018

The top two favorite blogs were KDNuggets and R Bloggers. Data Science/Analytics Tools, Technologies and Languages used in 2017. Data Science/Analytics Tools, Technologies and Languages used in 2017. A principal component analysis of the 20 challenges studied showed that challenges can be grouped into five categories.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74