IBM Big Data Hub

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

Machine Learning 72

Machine Learning Optimization Unstructured Data Sales 72

O'Reilly on Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. 2] The Security of Machine Learning. [3]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

Analytics Vidhya

NOVEMBER 25, 2020

Introduction Have you ever been tasked with visualizing the relationship between each. The post Creating Linear Model, It’s Equation and Visualization for Analysis appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

Visualization 284

Visualization Modeling Data Science Publishing 284

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 159

Data Science Deep Learning Statistics Machine Learning 159

BizAcuity

APRIL 1, 2023

1] With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. Refine the model: Machine learning applications require meticulous attention to optimize an algorithm.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. How Machine Learning Helps Detect and Prevent AML. OCR is widely used to digitize all kinds of physical documentation.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Smarten

APRIL 25, 2024

Whether you are trying to solve a business problem, get to the heart of that problem, find a business opportunity, predict the need for resources, new products or locations or understanding changes in your customer buying behavior, you don’t have time to learn complex tools or take training in analytics.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

CIO Business Intelligence

JANUARY 19, 2024

The US Bureau of Labor Statistics (BLS) forecasts employment of data scientists will grow 35% from 2022 to 2032, with about 17,000 openings projected on average each year. Companies are increasingly eager to hire data professionals who can make sense of the wide array of data the business collects.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

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

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 133

Data Analytics Diagnostic Analytics Management Analytics 133

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 131

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 131

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 139

Data Science Statistics Machine Learning Visualization 139

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

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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

JUNE 14, 2023

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization. Candidates have 90 minutes to complete the exam.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

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 295

Statistics Visualization Data Science Analytics 295

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 353

Statistics Analytics Structured Data Machine Learning 353

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

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 323

Statistics Analytics IT Machine Learning 323

CIO Business Intelligence

OCTOBER 13, 2023

The data architect is responsible for visualizing and designing an organization’s enterprise data management framework. Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

CIO Business Intelligence

NOVEMBER 14, 2022

Decision intelligence seeks to update and reinvent decision support systems with a sophisticated mix of tools including artificial intelligence (AI) and machine learning (ML) to help automate decision-making. Commonly used models include: Statistical models. They emphasize access to and manipulation of a model. Parmenides Edios.

Data mining 136

Data mining Data-driven Statistics OLAP 136

Smarten

JANUARY 30, 2024

The right self-serve data prep solution can provide easy-to-use yet sophisticated data prep tools that are suitable for your business users, and enable data preparation techniques like: Connect and Mash Up Auto Suggesting Relationships JOINS and Types Sampling and Outliers Exploration, Cleaning, Shaping Reducing and Combining Data Insights (Data Quality (..)

Analytics 67

Analytics Data Quality Visualization Metadata 67

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 306

Statistics Data Science Publishing Analytics 306

FineReport

MARCH 24, 2024

Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. They identify and interpret trends in complex datasets, optimize statistical results, and maintain databases while devising new data collection processes.

Statistics 52

Statistics Data mining Visualization Reporting 52

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 104

Data Science Statistics Deep Learning Machine Learning 104

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 143

Data mining Data Science Informatics Statistics 143

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 363

Data Science Machine Learning Analytics IT 363

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

Smart Data Collective

DECEMBER 19, 2021

The rise of machine learning and the use of Artificial Intelligence gradually increases the requirement of data processing. That’s because the machine learning projects go through and process a lot of data, and that data should come in the specified format to make it easier for the AI to catch and process.

Optimization 135

Optimization Machine Learning Data mining Statistics 135

Smart Data Collective

MARCH 27, 2023

Data Scientists and Analysts use various tools such as machine learning algorithms, statistical modeling, natural language processing (NLP), and predictive analytics to identify trends, uncover opportunities for improvement, and make better decisions. as this will set you apart from other applicants.

Data Science 91

Data Science Statistics Data-driven Machine Learning 91

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 Data-driven Big Data 350

CIO Business Intelligence

OCTOBER 13, 2023

It’s a role that requires experience with natural language processing , coding languages, statistical models, and large language and generative AI models. This role is responsible for training, developing, deploying, scheduling, monitoring, and improving scalable machine learning solutions in the enterprise.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

AWS Big Data

APRIL 3, 2024

AWS Glue is a serverless data integration service that allows you to visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes in Iceberg format. She is passionate about data integration and orchestration, serverless and big data processing, and machine learning.

Data Lake 91

Data Lake Snapshot Metadata Data Architecture 91

O'Reilly on Data

MARCH 26, 2024

This seems to be emerging as a feature, not a bug, and hopefully it’s obvious to you why they called their IEEE opinion piece Generative AI Has a Visual Plagiarism Problem. There are lots of conversations about whether or not LLMs (and machine learning, more generally) are forms of compression or not.

Modeling 275

Modeling Machine Learning Risk Advertising 275

Smart Data Collective

MAY 13, 2022

Most traditional business insight tools are no longer capable of processing and visualizing the growing volumes of complex data coming from various devices, channels, and business systems. AI and machine learning. Before you can have AI-driven apps, you need to train a machine learning model to do the work.

Business Analytics 134

Business Analytics Analytics Unstructured Data Data-driven 134

CIO Business Intelligence

AUGUST 14, 2023

Without visualized analytics, it was difficult to bridge the void between expectation and accurate analysis. The objectives were lofty: integrated, scalable, and replicable enterprise management; streamlined business processes; and visualized risk control, among other aims, all fully integrating finance, logistics, production, and sales.

Key Performance Indicator 97

Key Performance Indicator Sales Manufacturing KPI 97