Analytics Vidhya

JUNE 11, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Many engineers have never worked in statistics or data science. The post Know the basics of Exploratory Data Analysis appeared first on Analytics Vidhya.

Statistics 198

Statistics Data Science Publishing Analytics 198

FineReport

DECEMBER 11, 2019

In the past few years, the term “data science” has been widely used, and people seem to see it in every field. Big Data”, “Business Intelligence”, “ Data Analysis ” and “ Artificial Intelligence ” came into being. For a while, everyone seems to have begun to learn data analysis. From Google. About thinking.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

Analytics Vidhya

APRIL 23, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. When we learn Data Science as beginners we came across. The post 3 Central Tendency Measures – Mean, Mode, Median appeared first on Analytics Vidhya.

Measurement 301

Measurement Data Science Publishing Analytics 301

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. Visualizations are the best tools to make trends and general insights understandable.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

CIO Business Intelligence

NOVEMBER 14, 2022

With organizations increasingly focused on data-driven decision making, decision science (or decision intelligence) is on the rise, and decision scientists may be the key to unlocking the potential of decision science systems. Commonly used models include: Statistical models. Parmenides Edios.

Data mining 144

Data mining Data-driven Statistics OLAP 144

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Analytics Vidhya

JUNE 10, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Exploratory data analysis is an approach to analyzing data sets. The post Exploratory Data Analysis : A Beginners Guide To Perform EDA appeared first on Analytics Vidhya.

Data Science 212

Data Science Publishing Analytics Structured Data 212

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

Data Science 101

OCTOBER 31, 2019

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Note: Data Science 101 is proud to have this sponsored post from Data Science Dojo.

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Data mining KDD Data Science Forecasting 77

datapine

AUGUST 29, 2022

With that in mind, we have prepared a list of the top 19 definitive data analytics and big data books, along with magazines and authentic readers’ reviews upvoted by the Goodreads community. Essential Big Data And Data Analytics Insights. Discover The Best Data Analytics And Big Data Books Of All Time.

Big Data 263

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Domino Data Lab

JANUARY 6, 2019

In Paco Nathan ‘s latest column, he explores the theme of “learning data science” by diving into education programs, learning materials, educational approaches, as well as perceptions about education. He is also the Co-Chair of the upcoming Data Science Leaders Summit, Rev. Learning Data Science.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

Insight

MARCH 12, 2020

There was only one problem: literary agents, the gatekeepers of the publishing industry, kept rejecting the book?—?often 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. often without even looking at it.

Modeling 59

Modeling Metadata Publishing Sales 59

DataKitchen

MAY 10, 2021

And the worst part – data errors take the fun out of data science. Remember your first data science courses? You probably imagined your career would be about helping drive insights with data instead of having to sit in endless meetings discussing analytics errors and painstaking corrective actions.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Edwin Chen

SEPTEMBER 6, 2011

tl;dr See this movie visualization for a case study on how a post propagates through Quora. Here’s a visualization I made of upvotes on my answer across time (click here for a larger view). For another view of the upvote dynamics, here’s a static visualization, where we can again easily see the clusters of activity: Fin.

Machine Learning 52

Machine Learning Broadcasting Visualization Data mining 52

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. ML model interpretability and data visualization. back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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. Data science. Session Summary.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Domino Data Lab

OCTOBER 23, 2019

As Domino is committed to supporting data scientists and accelerating research, we reached out to Addison-Wesley Professional (AWP) Pearson for the appropriate permissions to excerpt “Predicting Social-Media Influence in the NBA” from the book, Pragmatic AI: An Introduction to Cloud-Based Machine Learning by Noah Gift. In Figure 6.1,

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

OCTOBER 9, 2019

As Domino seeks to support the acceleration of data science work, including core tasks, Domino reached out to Addison-Wesley Professional (AWP) Pearson for the appropriate permissions to except “Clustering” from the book, R for Everyone: Advanced Analytics and Graphics, Second Edition.

Statistics 100

Statistics Machine Learning Metrics Measurement 100

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

AUGUST 20, 2019

Many thanks to AWP Pearson for the permission to excerpt “Manual Feature Engineering: Manipulating Data for Fun and Profit” from the book, Machine Learning with Python for Everyone by Mark E. We discussed this as far back as Chapter 1 [in the book]. There is also a complementary Domino project available.

Testing 68

Testing Modeling Interactive Measurement 68

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. Utilizing NLP helps researchers and data scientists complete core tasks faster. and 2.6) [ in the book]. Introduction.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Smarten

APRIL 19, 2022

They can analyze how product opinions change over time and understand sentiments to improve the response to product reviews, movie or book reviews, advertising campaigns, Amazon product reviews, social media tweets and comments, news headlines media content, and more.

Slice and Dice 57

Slice and Dice Business Intelligence Advertising Predictive Modeling 57

Domino Data Lab

SEPTEMBER 25, 2019

Conducting exploratory analysis and extracting meaningful insights from data are core components of research and data science work. Time series data is commonly encountered. We see it when working with log data, financial data, transactional data, and when measuring anything in a real engineering system.

Forecasting 87

Forecasting Modeling Statistics Optimization 87

Domino Data Lab

MARCH 27, 2019

Special thanks to Addison-Wesley Professional for permission to excerpt the following “Manipulating data with dplyr” chapter from the book, Programming Skills for Data Science: Start Writing Code to Wrangle, Analyze, and Visualize Data with R. Data scientists spend countless hours wrangling data.

Statistics 85

Statistics Data Science Visualization IT 85

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. For example, streaming data from sensors to an analytics platform where it is processed and visualized immediately.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52