MACHINE LEARNING

Machine Learning For Data Analytics

INTRODUCTION

HOW DOES MACHINE LEARNING WORK?

TYPES OF MACHINE LEARNING

USES OF ML IN ANALYTICS

• Identify patterns in data
• Make predictions about future events
• Cluster data into groups
• Reduce the dimensionality of data
• Improve the accuracy of data models

CHALLENGES OF ML IN ANALYTICS

• It can be difficult to find and prepare the data that is needed to train the algorithms.
• Machine Learning algorithms can be computationally expensive to train and run.
• Some of the algorithms are difficult to interpret even though they work well.

FUTURE OF MACHINE LEARNING IN ANALYTICS

• Machine learning is a rapidly evolving field, and there are many new developments in this area.
• As machine learning algorithms become more powerful and efficient, they will be used for a wider range of data analytics tasks.
• Machine learning will also be used to automate more tasks that are currently done manually.