Smart Data Collective

NOVEMBER 1, 2020

Machines, artificial intelligence (AI), and unsupervised learning are reshaping the way businesses vie for a place under the sun. With that being said, let’s have a closer look at how unsupervised machine learning is omnipresent in all industries. What Is Unsupervised Machine Learning?

Machine Learning 145

Machine Learning Data mining Visualization Statistics 145

Analytics Vidhya

MAY 7, 2019

Introduction I love descriptive statistics. Visualizing data and analyzing trends is one of the most exciting aspects of any data science project. The post Extracting and Analyzing 1000 Basketball Games using Pandas and Chartify appeared first on Analytics Vidhya.

Statistics 296

Statistics Visualization Data Science Analytics 296

Analytics Vidhya

DECEMBER 25, 2020

ArticleVideos Image by Author In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. The post Using Predictive Power Score to Pinpoint Non-linear Correlations appeared first on Analytics Vidhya.

Statistics 361

Statistics Analytics Structured Data Machine Learning 361

Smart Data Collective

SEPTEMBER 13, 2023

Machine Learning is Crucial for Success in Digital Marketing If you have a Spotify or Netflix account, you have probably noticed a trend. If yes, then you will be amazed to learn that this is all machine learning. Now read on to learn more about machine learning and digital marketing.

Machine Learning 124

Machine Learning Marketing Strategy Optimization 124

datapine

MAY 14, 2019

We gave you a curated list of our top 15 data analytics books , top 18 data visualization books , top 16 SQL books – and, as promised, we’re going to tell you all about the world’s best books on data science. 2) “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courville. click for book source**.

Data Science 350

Data Science Machine Learning Big Data Data-driven 350

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. It helps to automate and makes the usage of the R programming statistical language easier and much more effective. perfect for statistical computing and design.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Smart Data Collective

NOVEMBER 9, 2022

There are a number of great applications of machine learning. The main purpose of machine learning is to partially or completely replace manual testing. Machine learning makes it possible to fully automate the work of testers in carrying out complex analytical processes. Top ML Companies.

Machine Learning 122

Machine Learning Testing Cost-Benefit Data-driven 122

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2) Data Discovery/Visualization. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Analytics Vidhya

FEBRUARY 24, 2021

ArticleVideo Book Introduction to Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and its sub-field Machine Learning (ML) have taken the world by storm. The post A Comprehensive Step-by-Step Guide to Become an Industry Ready Data Science Professional appeared first on Analytics Vidhya.

Data Science 378

Data Science Machine Learning Analytics IT 378

CIO Business Intelligence

FEBRUARY 6, 2025

Imagine generating complex narratives from data visualizations or using conversational BI tools that respond to your queries in real time. Tableau, Qlik and Power BI can handle interactive dashboards and visualizations. Even basic predictive modeling can be done with lightweight machine learning in Python or R.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

KDnuggets

OCTOBER 10, 2022

It includes SQL, web scraping, statistics, data wrangling and visualization, business intelligence, machine learning, deep learning, NLP, and super cheat sheets. The only cheat you need for a job interview and data professional life.

Data Science 160

Data Science Deep Learning Statistics Machine Learning 160

datapine

MARCH 25, 2019

Conduct statistical analysis. One of the most pivotal types of data analysis methods is statistical analysis. Regression: A definitive set of statistical processes centered on estimating the relationships among particular variables to gain a deeper understanding of particular trends or patterns. Visualize your data.

Key Performance Indicator 217

Key Performance Indicator Statistics Big Data Visualization 217

Analytics Vidhya

JUNE 20, 2023

According to the Bureau of Labor Statistics (BLS), the employment of research analysts, including data analysts, is projected to increase by 23% from 2021 to 2031. This significant growth in data analysis careers presents promising prospects for aspiring candidates. It profoundly impacts the services and products provided to the public.

Statistics 337

Statistics Analytics IT Machine Learning 337

Analytics Vidhya

OCTOBER 10, 2022

We use summary statistics and graphical tools to get to know our data and understand what we may deduce from them during EDA. […]. Introduction Exploratory Data Analysis, or EDA, examines the data and identifies potential relationships between variables using numerical summaries and visualisations.

Statistics 319

Statistics Data Science Publishing Analytics 319

Analytics Vidhya

APRIL 16, 2019

I have relied on it since my days of learning statistics back in. Introduction I’m a big fan of R – it’s no secret. The post 8 Useful R Packages for Data Science You Aren’t Using (But Should!) appeared first on Analytics Vidhya.

Data Science 308

Data Science Statistics Analytics IT 308

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. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Smarten

NOVEMBER 26, 2024

The business can harness the power of statistics and machine learning to uncover those crucial nuggets of information that drive effective decision, and to improve the overall quality of data. Discover the power of Augmented Analytics , machine learning, and Natural Language Processing (NLP).

Machine Learning 64

Machine Learning Data Quality Predictive Modeling Metadata 64

AWS Big Data

DECEMBER 4, 2024

Extract, transform, and load (ETL) is the process of combining, cleaning, and normalizing data from different sources to prepare it for analytics, artificial intelligence (AI), and machine learning (ML) workloads. For each table ingested by the zero-ETL integration, two groups of logs are created: status and statistics.

Data Integration 114

Data Integration Data Lake Statistics Data-driven 114

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. But let’s see in more detail what experts say and how can we connect and differentiate the both.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Sisense

SEPTEMBER 25, 2020

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. No matter your skill, career level, or title, the ability to analyze, organize, and visualize data are vital skills in our world of quickly growing and ever-changing data. Statistics and programming go hand in hand.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Visual IDE for data pipelines; RPA for rote tasks.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

datapine

JANUARY 6, 2022

Through the art of streamlined visual communication, data dashboards permit businesses to engage in real-time and informed decision-making and are key instruments in data interpretation. More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. agree, strongly agree, disagree, etc.).

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Sisense

JUNE 30, 2020

In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. Data visualization and visual analytics are two terms that come up a lot when new and experienced analytics users alike delve into the world of data in their quest to make smarter decisions.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Tableau: Now owned by Salesforce, Tableau is a data visualization tool. js: This JavaScript library is used to make interactive visualizations in web browsers.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Business analytics also involves data mining, statistical analysis, predictive modeling, and the like, but is focused on driving better business decisions.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Analytics Vidhya

NOVEMBER 6, 2020

Introduction to Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and its sub-field Machine Learning (ML) have taken the world by storm. The post A Comprehensive Step-by-Step Guide to Become an Industry-Ready Data Science Professional appeared first on Analytics Vidhya.

Data Science 264

Data Science Machine Learning Analytics IT 264

Analytics Vidhya

FEBRUARY 4, 2022

Overview Motivation to Learn R Covering the BASICS & MUST KNOW Concepts in R Introduction Since you are reading this article, I am assuming that right now you are in your journey of becoming a data scientist. There is a high possibility that you already are aware of some of the data visualization and analytics […].

Visualization 289

Visualization Analytics Deep Learning Statistics 289

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. It culminates with a capstone project that requires creating a machine learning model.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

CIO Business Intelligence

FEBRUARY 20, 2025

In addition, they can use statistical methods, algorithms and machine learning to more easily establish correlations and patterns, and thus make predictions about future developments and scenarios. A central measure here is the definition and visualization of control and monitoring key figures.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

datapine

NOVEMBER 19, 2019

Exciting and futuristic, the concept of computer vision is based on computing devices or programs gaining the ability to extract detailed information from visual images. Visual analytics: Around three million images are uploaded to social media every single day. Artificial Intelligence (AI).

Technology 279

Technology Internet of Things IT IoT 279

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. Introduction Machine learning models often behave unpredictably, as data scientists would be the first to tell you.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

Smart Data Collective

NOVEMBER 18, 2020

The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Previously, such problems were dealt with by specialists in mathematics and statistics. Statistics, mathematics, linear algebra. Machine learning. Where to Use Data Science?

Data mining 144

Data mining Data Science Informatics Statistics 144

Smart Data Collective

JUNE 4, 2021

Data science needs knowledge from a variety of fields including statistics, mathematics, programming, and transforming data. Mathematics, statistics, and programming are pillars of data science. In data science, use linear algebra for understanding the statistical graphs. It is the building block of statistics.

Data Science 133

Data Science Statistics Deep Learning Machine Learning 133

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) Industry 4.0

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 73

Machine Learning Modeling Deep Learning Predictive Modeling 73

Sisense

JUNE 26, 2020

The human brain processes visual data better than any other kind of data, which is good because about 90% of the information our brains process is visual. Visual processing and responses both occur more quickly compared to other stimuli. The brain processes data in visuals or images faster than data in text or rows of numbers.

Visualization 97

Visualization Unstructured Data Measurement Data-driven 97