1st Edition
by Rohit Raja (Editor), Kapil Kumar Nagwanshi (Editor), Sandeep Kumar (Editor), K. Ramya Laxmi (Editor)
DATA MINING AND MACHINE LEARNING APPLICATIONS
The
book elaborates in detail on the current needs of data mining and
machine learning and promotes mutual understanding among research in
different disciplines, thus facilitating research development and
collaboration.
Data, the latest currency of today’s
world, is the new gold. In this new form of gold, the most beautiful
jewels are data analytics and machine learning. Data mining and machine
learning are considered interdisciplinary fields. Data mining is a
subset of data analytics and machine learning involves the use of
algorithms that automatically improve through experience based on data.
Massive
datasets can be classified and clustered to obtain accurate results.
The most common technologies used include classification and clustering
methods. Accuracy and error rates are calculated for regression and
classification and clustering to find actual results through algorithms
like support vector machines and neural networks with forward and
backward propagation. Applications include fraud detection, image
processing, medical diagnosis, weather prediction, e-commerce and so
forth.
The book features:
- A review of the state-of-the-art in data mining and machine learning,
- A review and description of the learning methods in human-computer interaction,
- Implementation
strategies and future research directions used to meet the design and
application requirements of several modern and real-time applications
for a long time,
- The scope and implementation of a majority of data mining and machine learning strategies.
- A discussion of real-time problems.
Audience
Industry
and academic researchers, scientists, and engineers in information
technology, data science and machine and deep learning, as well as
artificial intelligence more broadly.