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. The applications of predictive analytics are extensive and often require four key components to maintain effectiveness. Data Sourcing.

Predictive Analytics 139

Predictive Analytics Analytics Analytics Decision Trees 139

DagsHub

JULY 25, 2024

Source: Author Introduction Deep learning, a branch of machine learning inspired by biological neural networks, has become a key technique in artificial intelligence (AI) applications. Deep learning methods use multi-layer artificial neural networks to extract intricate patterns from large data sets.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. RPA and ML are two different technologies that serve different purposes.

ML 133

ML ML Machine Learning Machine Learning 133

Data Science Dojo

AUGUST 16, 2024

Generative AI for Data Analytics – Understanding the Impact To understand the impact of generative AI for data analytics, it’s crucial to dive into the underlying mechanisms, that go beyond basic automation and touch on complex statistical modeling, deep learning, and interaction paradigms.

Analytics 195

Analytics Analytics Power BI AI 195

Towards AI

JUNE 27, 2023

RapidMiner RapidMiner, a renowned player in the realm of machine learning tools, offers an all-encompassing platform for a myriad of operations. Its functionalities span from deep learning to text mining, data preparation, and predictive analytics, ensuring a versatile utility for developers and data scientists alike.

Machine Learning 98

Machine Learning Machine Learning ML ML 98

Towards AI

JULY 19, 2023

Please refer to Part 1– to understand what is Sales Prediction/Forecasting, the Basic concepts of Time series modeling, and EDA I’m working on Part 3 where I will be implementing Deep Learning and Part 4 where I will be implementing a supervised ML model. Data Preparation — Collect data, Understand features 2.

Cross Validation 98

Cross Validation Clustering EDA Data Preparation 98

Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. RPA and ML are two different technologies that serve different purposes.

ML 70

ML ML Machine Learning Machine Learning 70