Analytics Vidhya

DECEMBER 13, 2021

Pursuing any data science project will help you polish your resume. The post Top Data Science Projects to add to your Portfolio in 2021 appeared first on Analytics Vidhya. Introduction 2021 is a year that proved nothing is better than a Proof of Work to evaluate any candidate’s worth, initiative, and skill.

Data Science 343

Data Science Analytics Data mining Deep Learning 343

datapine

MAY 14, 2019

By gaining the ability to understand, quantify, and leverage the power of online data analysis to your advantage, you will gain a wealth of invaluable insights that will help your business flourish. The ever-evolving, ever-expanding discipline of data science is relevant to almost every sector or industry imaginable – on a global scale.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Analytics Vidhya

DECEMBER 23, 2021

This article was published as a part of the Data Science Blogathon Optimization Optimization provides a way to minimize the loss function. Optimization aims to reduce training errors, and Deep Learning Optimization is concerned with finding a suitable model. In this article, we will […].

Optimization 332

Optimization Modeling Deep Learning Data Science 332

Smart Data Collective

JUNE 10, 2022

Are you interested in a career in data science? The Bureau of Labor Statistics reports that there are over 105,000 data scientists in the United States. The average data scientist earns over $108,000 a year. Data Scientist. Machine Learning Engineer. Data Architect.

Data Science 119

Data Science Machine Learning Statistics Business Intelligence 119

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 338

Data Science Machine Learning Analytics IT 338

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

CIO Business Intelligence

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Analytics Vidhya

MAY 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In Machine learning or Deep Learning, some of the models. The post How to transform features into Normal/Gaussian Distribution appeared first on Analytics Vidhya.

Deep Learning 318

Deep Learning Machine Learning Data Science Publishing 318

Domino Data Lab

JULY 10, 2019

New tools are constantly being added to the deep learning ecosystem. For example, there have been multiple promising tools created recently that have Python APIs, are built on top of TensorFlow or PyTorch , and encapsulate deep learning best practices to allow data scientists to speed up research.

Deep Learning 110

Deep Learning Visualization Recreation/Entertainment Data Processing 110

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 254

Data Science Machine Learning Analytics IT 254

Analytics Vidhya

FEBRUARY 23, 2023

Introduction Data analysts with the technological know-how to tackle challenging problems are data scientists. They collect, analyze, interpret data, and handle statistics, mathematics, and computer science. They are accountable for providing insights that go beyond statistical analyses.

Statistics 312

Statistics Technology Analytics Deep Learning 312

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 58

Data Science Machine Learning Cost-Benefit Deep Learning 58

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 122

Predictive Analytics Analytics Predictive Modeling Data mining 122

Analytics Vidhya

JUNE 5, 2023

In today’s data-driven world, data scientists play a crucial role in helping businesses make informed decisions by analyzing and interpreting data.

Strategy 256

Strategy Statistics Machine Learning Data-driven 256

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. Its value is so significant that scaling data science has become the new business imperative with organizations spending tens of millions of dollars on data, technology and talent. What are Data Scientists?

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Rocket-Powered Data Science

APRIL 25, 2019

A few years ago, I generated a list of places to receive data science training. Learn the what, why, and how of Data Science and Machine Learning here. Learn the what, why, and how of Data Science and Machine Learning here. That list has become a bit stale.

Data Science 38

Data Science Machine Learning Deep Learning Statistics 38

Sisense

APRIL 15, 2021

Analytics is the future. Your company is gathering data (and has likely been doing so for years), and you’ve probably got a system or two to glean insights from that data to make smarter decisions. The good news is that augmented analytics will make your life a lot easier! Simplify analytics with AI.

Analytics 98

Analytics Data Science Modeling Machine Learning 98

CIO Business Intelligence

JANUARY 25, 2024

That doesn’t mean getting certifications in deep learning or mastering natural language processing. Understand data The people driving innovation in any organization have to be passionate about data and its possibilities. “We Along these lines, predictive analytics is one field destined for AI-powered growth.

Deep Learning 115

Deep Learning Cost-Benefit Statistics Manufacturing 115

CIO Business Intelligence

OCTOBER 13, 2023

In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool. 1989 to be exact. The details are below.

KDD 81

KDD Knowledge Discovery Data mining Statistics 81

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

Occam's Razor

MARCH 30, 2017

It’s implications are far and wide, even in the narrow scope that I live in (marketing, analytics, influence). Machine Learning | Marketing. Machine Learning | Analytics. People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

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

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. The simplest answer is that these terms refer to some of the many analytic methods available to Data Scientists.

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

Business Over Broadway

SEPTEMBER 5, 2018

Even though natural events such as floods, earthquakes or hurricanes are inevitable, I believe that their impact can be mitigated through the application of data and analytics. Data is the Fuel; Data Science is the Engine. If you understand the data, you understand the process that generates them.

Data Science 57

Data Science Statistics Advertising Deep Learning 57

O'Reilly on Data

JUNE 18, 2019

“AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. As model building become easier, the problem of high-quality data becomes more evident than ever. business and quality rules, policies, statistical signals in the data, etc.).

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

Cloudera

FEBRUARY 25, 2021

Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. Additionally, the AMPs catalog within CML is completely customizable, enabling your data science teams to build and securely share internal projects as AMPs.

Deep Learning 83

Deep Learning Machine Learning Forecasting Visualization 83

IBM Big Data Hub

NOVEMBER 29, 2023

For instance, if a business prioritizes accuracy in generating synthetic data, the resulting output may inadvertently include too many personally identifiable attributes, thereby increasing the company’s privacy risk exposure unknowingly. How to get started with synthetic data in watsonx.ai

Metrics 88

Metrics Machine Learning Risk Statistics 88

Analytics Vidhya

APRIL 11, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. First, The post Introduction to Autonomous Navigation – LIDAR, Sensor Fusion, Kalman Filter appeared first on Analytics Vidhya. Introduction This article is an introduction to autonomous navigation.

Data Science 198

Data Science Publishing Analytics Deep Learning 198

IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Generative AI uses advanced machine learning algorithms and techniques to analyze patterns and build statistical models.

Enterprise 125

Enterprise Modeling Testing Data-driven 125

Domino Data Lab

OCTOBER 7, 2020

Statistical methods for analyzing this two-dimensional data exist. This statistical test is correct because the data are (presumably) bivariate normal. When there are many variables the Curse of Dimensionality changes the behavior of data and standard statistical methods give the wrong answers.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

O'Reilly on Data

JULY 28, 2020

There’s a substantial literature about ethics, data, and AI, so rather than repeat that discussion, we’ll leave you with a few resources. Ethics and Data Science is a short book that helps developers think through data problems, and includes a checklist that team members should revisit throughout the process.

Marketing 362

Marketing Experimentation Metrics Testing 362

FineReport

DECEMBER 19, 2019

It can be used as a portal for data reporting, or as a platform for business analysis. For newbies, a tool with low learning difficulty but powerful analytical performance cannot be better. Pandas is a Python data science library that is constantly improving. Its data structure is very suitable for data processing.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

bridgei2i

OCTOBER 7, 2020

Underwriting essentially means evaluating the risk proposition of an insurance cover and determining how much an insurer should charge for the same by studying historical data and statistical models. But the sheer volume of data might cloud manual judgments and here is where automation and digitization could help.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

IBM Big Data Hub

APRIL 18, 2024

Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.

Cost-Benefit 96

Cost-Benefit Modeling Manufacturing Interactive 96