Analytics Vidhya

OCTOBER 28, 2022

Introduction The generalization of machine learning models is the ability of a model to classify or forecast new data. When we train a model on a dataset, and the model is provided with new data absent from the trained set, it may perform […].

Machine Learning 398

Machine Learning Modeling Forecasting Data Science 398

Smart Data Collective

FEBRUARY 23, 2023

Data mining technology is one of the most effective ways to do this. By analyzing data and extracting useful insights, brands can make informed decisions to optimize their branding strategies. This article will explore data mining and how it can help online brands with brand optimization. What is Data Mining?

Data mining 123

Data mining Optimization Technology Marketing 123

Analytics Vidhya

OCTOBER 1, 2020

Overview Feature engineering techniques are a must know concept for machine learning professionals Here are 7 feature engineering techniques you can start using right. The post 7 Feature Engineering Techniques in Machine Learning You Should Know appeared first on Analytics Vidhya.

Machine Learning 400

Machine Learning Analytics Data mining 400

Analytics Vidhya

APRIL 29, 2020

Overview Deploying your machine learning model is a key aspect of every ML project Learn how to use Flask to deploy a machine learning. The post How to Deploy Machine Learning Models using Flask (with Code!) appeared first on Analytics Vidhya.

Machine Learning 395

Machine Learning Modeling Analytics Data mining 395

Smart Data Collective

NOVEMBER 18, 2020

You may not even know exactly which path you should pursue, since some seemingly similar fields in the data technology sector have surprising differences. We decided to cover some of the most important differences between Data Mining vs Data Science in order to finally understand which is which. What is Data Science?

Data mining 142

Data mining Data Science Informatics Statistics 142

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? Source ].

Machine Learning 130

Machine Learning Data mining Visualization Statistics 130

Domino Data Lab

MARCH 11, 2021

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. Machine learning is used in almost every industry, notably finance , insurance , healthcare , and marketing. How to choose the right ML Framework.

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

Smart Data Collective

JUNE 24, 2023

Fortunately, new advances in machine learning technology can help mitigate many of these risks. Therefore, you will want to make sure that your cryptocurrency wallet or service is protected by machine learning technology. In 2018, researchers used data mining and machine learning to detect Ponzi schemes in Ethereum.

Machine Learning 74

Machine Learning Broadcasting Risk Data mining 74

Smart Data Collective

JULY 8, 2021

It is important to be informed about the potential benefits of machine learning as a consumer. Before you can understand the benefits that machine learning offers to you as a customer, it is a good idea to see how it is affecting the industry. There are a number of online machine learning tools that can help you.

Machine Learning 143

Machine Learning Management Finance Cost-Benefit 143

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). Machine learning provides the technical basis for data mining.

Data mining 77

Data mining KDD Data Science Forecasting 77

KDnuggets

JUNE 15, 2022

14 Essential Git Commands for Data Scientists; A Structured Approach To Building a Machine Learning Model; How is Data Mining Different from Machine Learning?; Understanding Functions for Data Science; Top 18 Data Science Facebook Groups.

Machine Learning 97

Machine Learning Data mining Modeling Data Science 97

Rocket-Powered Data Science

DECEMBER 16, 2018

The above example (clustering) is taken from unsupervised machine learning (where there are no labels on the training data). There are also examples of cold start in supervised machine learning (where you do have class labels on the training data). Genetic Algorithms (GAs) are an example of meta-learning.

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

Analytics Vidhya

JANUARY 28, 2022

Image Source: Author Introduction Data Engineers and Data Scientists need data for their Day-to-Day job. Of course, It could be for Data Analytics, Data Prediction, Data Mining, Building Machine Learning Models Etc.,

Data Science 310

Data Science Data mining Machine Learning Publishing 310

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 58

Machine Learning Data Science Statistics Deep Learning 58

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. Rapidminer Studio is its visual workflow designer for the creation of predictive models.

Data Science 319

Data Science Data Lake Data mining Deep Learning 319

Smart Data Collective

AUGUST 20, 2021

As we said in the past, big data and machine learning technology can be invaluable in the realm of software development. Machine learning technology has become a lot more important in the app development profession. Machine learning can be surprisingly useful when it comes to monetizing apps.

Machine Learning 87

Machine Learning Advertising Data mining Deep Learning 87

KDnuggets

DECEMBER 13, 2021

So much of data science and machine learning is founded on having clean and well-understood data sources that it is unsurprising that the data labeling market is growing faster than ever.

Machine Learning 154

Machine Learning Marketing Data Science Data mining 154

Decision Management Solutions

DECEMBER 8, 2020

Enterprises today are eager to apply machine learning to improve their operations. Machine learning can improve operations, but only when its predictive models are deployed, integrated, and—most importantly—acted upon. Take a decision-centric and business-focused approach to machine learning projects.

Machine Learning 52

Machine Learning Data mining Predictive Modeling Data-driven 52

Analytics Vidhya

DECEMBER 27, 2023

Introduction Data annotation plays a crucial role in the field of machine learning, enabling the development of accurate and reliable models. In this article, we will explore the various aspects of data annotation, including its importance, types, tools, and techniques.

Machine Learning 315

Machine Learning Modeling Analytics Data mining 315

Analytics Vidhya

JULY 12, 2023

One often encounters datasets with categorical variables in data analysis and machine learning. However, many machine learning algorithms require numerical input. These variables represent qualitative attributes rather than numerical values. This is where label encoding comes into play.

Machine Learning 263

Machine Learning Analytics Data mining 263

KDnuggets

DECEMBER 13, 2021

So much of data science and machine learning is founded on having clean and well-understood data sources that it is unsurprising that the data labeling market is growing faster than ever.

Machine Learning 83

Machine Learning Marketing Data Science Data mining 83

BizAcuity

APRIL 19, 2019

The answer lies in revolutionary machine learning and business analytics. Adaptive machine and business analytics, applying cutting-edge machine learning and other technologies are proving helpful in spotting anomalies among users in real-time and fighting this issue. ML and Business Analytics to the rescue.

Machine Learning 75

Machine Learning Metrics Data mining Business Analytics 75

Analytics Vidhya

MAY 4, 2022

This article was published as a part of the Data Science Blogathon. Introduction Text Mining is also known as Text Data Mining or Text Analytics or is an artificial intelligence (AI) technology that uses natural language processing (NLP) to extract essential data from standard language text.

Unstructured Data 287

Unstructured Data Data mining Data Science Publishing 287

Jen Stirrup

SEPTEMBER 30, 2021

Although CRISP-DM is not perfect , the CRISP-DM framework offers a pathway for machine learning using AzureML for Microsoft Data Platform professionals. AI vs ML vs Data Science vs Business Intelligence. They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

CIO Business Intelligence

JULY 5, 2022

Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. The discipline is a key facet of the business analyst role. Business analytics techniques.

Business Analytics 135

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 135

CIO Business Intelligence

JANUARY 19, 2024

The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

TDAN

AUGUST 17, 2021

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

Predictive Modeling 115

Predictive Modeling Modeling Data mining Big Data 115

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.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

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 Data Science 81

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 132

Optimization Machine Learning Data mining Statistics 132

CIO Business Intelligence

JUNE 7, 2022

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. What are the four types of data analytics? Data analytics methods and techniques. Data analytics vs. business analytics.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

FineReport

MAY 6, 2020

Software Pemvisualisasi Data: excel, python, software profesional lainnya. Framework Big Data Processing: Hadoop, storm, spark. Data Warehous: SSIS, SSAS. Machine learning. Skill Data Mining: Matlab, R, Python. Seperti yang Anda ketahui, statistik adalah dasar analisis data. Machine Learning.

Data mining 98

Data mining Data Warehouse Machine Learning Big Data 98

CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems are generally recognized as one element of business intelligence systems, along with data warehousing and data mining. These systems are often paired with data mining to sift through databases to produce data content relationships. Some experts consider BI a successor to DSS.

Data mining 143

Data mining Data-driven Statistics Dashboards 143

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)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Smart Data Collective

JULY 7, 2022

Analytics Insight has touched on some of the benefits of using data analytics to make better stock market trades. They point out that value investors are using machine learning technology to anticipate future stock prices. You can find a number of great ways to reduce debt with data analytics. Optimize Your Investments.

Marketing 140

Marketing Data Analytics Analytics ROI 140

Analytics Vidhya

OCTOBER 8, 2021

This article was published as a part of the Data Science Blogathon Gathering and getting ready datasets is one of the critical techniques in any Machine learning project. But when we want to extract any internet site data when […].

Machine Learning 284

Machine Learning Data Science Publishing Analytics 284

Smart Data Collective

NOVEMBER 11, 2021

Data analytics technology can help immensely at this and all subsequent stages. Set Goals and Develop a Strategy with Data Mining. This is one of the most important ways that big data can help. You may not need to use data mining to outline your goals, but you will probably need this technology to conceptualize them.

B2B 109

B2B Data mining Big Data Marketing 109