Remove Data mining Remove Deep Learning Remove Optimization Remove Visualization
article thumbnail

Rapidminer Platform Supports Entire Data Science Lifecycle

David Menninger's Analyst Perspectives

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.

article thumbnail

12 data science certifications that will pay off

CIO Business Intelligence

The certification consists of several exams that cover topics such as machine learning, natural language processing, computer vision, and model forecasting and optimization. You should also have experience with pattern detection, experimentation in business optimization techniques, and time-series forecasting.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

An Important Guide To Unsupervised Machine Learning

Smart Data Collective

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? If you’ve ever come across deep learning, you might have heard about two methods to teach machines: supervised and unsupervised. Source ].

article thumbnail

Increasing Real-Time Efficiency Through AIOps

CIO Business Intelligence

In this way, AIOps frees up decision makers to focus on larger business issues, as well as provides them with clear visual information. There are several factors that can reduce organizational efficiency: Infrastructure: Many IT environments have disparate systems in silos, making it difficult to accelerate the flow of data between systems.

article thumbnail

Predictive Analytics: 4 Primary Aspects of Predictive Analytics

Smart Data Collective

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.

article thumbnail

Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining. appeared first on IBM Blog.

article thumbnail

Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Data analysis and interpretation The next step is to examine the extracted patterns, trends and insights to develop meaningful conclusions.