The dawn of this age of data and information has led to the computerization of society and the development of data collection and storage tools. With the help of this data, different algorithms and techniques can be used for discovering patterns and trends in huge volumes of data. This process is known as data mining. A Programmer’s Guide to Data Mining offers an in-depth look into the field of data mining. Apart from the important concepts in data mining, the book also explains these concepts with the help of Python, which is one of the most popular programming languages. You will also be taken step-by-step through the code for better understanding. Along with the conceptual and practical description of clustering and anomaly detection, you will help then be able to use these data mining concepts in other fields.
By the end of the book, you will be thorough with all the concepts regarding data mining and also be able to implement them with the help of Python.
What you will learn:
• Introduction to data mining and its various concepts.
• Data visualization and processing.
• Learn the importance of statistics in data mining.
• Learn about the different algorithms in data mining and their implementation with the help of Python.
• Cluster Analysis and detection of Anomalies with the help of Python.
• Data Cube Technology
• Future data mining trends and research frontiers.
Who the book is for:
Programmers looking to implement data mining algorithms with the help of Python will love the book. Budding students looking for the best introduction into the field of data mining and who want to quickly get to grips with the different aspects of data mining will also find the book very useful.
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