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

KDnuggets

JUNE 8, 2022

How about we take a closer look at data mining and machine learning so we know how to catch their different ends?

Data mining 156

Data mining Machine Learning 156

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 341

Data Science Data Lake Data mining Deep Learning 341

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 336

Data Science Data mining Machine Learning Publishing 336

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

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 144

Data mining Data Science Informatics Statistics 144

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 145

Data mining Optimization Technology Marketing 145

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 145

Machine Learning Data mining Visualization Statistics 145

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

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

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 158

Machine Learning Marketing Data Science Data mining 158

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 304

Unstructured Data Data mining Data Science Publishing 304

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 Knowledge Discovery 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 112

Machine Learning Data mining Modeling Data Science 112

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 334

Machine Learning Modeling Analytics Data mining 334

datapine

MAY 14, 2019

This interdisciplinary field of scientific methods, processes, and systems helps people extract knowledge or insights from data in a host of forms, either structured or unstructured, similar to data mining. 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

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 98

Machine Learning Broadcasting Risk Data mining 98

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 269

Machine Learning Analytics Data mining 269

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 90

Machine Learning Data mining Advertising Deep Learning 90

Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase.

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

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 291

Machine Learning Data Science Publishing Analytics 291

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

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

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

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 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

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 141

Optimization Machine Learning Data mining Statistics 141

datapine

NOVEMBER 27, 2019

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. 1 for data analytics trends in 2020.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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

Rocket-Powered Data Science

APRIL 25, 2019

Learn the what, why, and how of Data Science and Machine Learning here. Follow Kirk Borne on Twitter @KirkDBorne.

Data Science 38

Data Science Machine Learning Deep Learning Statistics 38

Smarten

FEBRUARY 19, 2025

Predictive analytics encompasses techniques like data mining, machine learning (ML) and predictive modeling techniques like time series forecasting, classification, association, correlation, clustering, hypothesis testing and descriptive statistics to analyze current and historical data and predict future events, results and business direction.

Predictive Analytics 64

Predictive Analytics Analytics Predictive Modeling Forecasting 64

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

Smart Data Collective

MAY 3, 2021

You should understand the changes wrought by big data and the impact that it is having on the gig economy. Let us take a look at some of the pros and cons of the world of gigs: #1 Unbridled liberty of choice with data mining. Big data has made it easier to identify new opportunities in the gig economy.

Big Data 130

Big Data Data mining Cost-Benefit Insurance 130

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

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 144

Data mining Data-driven Statistics OLAP 144

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

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 132

B2B Data mining Big Data Marketing 132