This book presents machine learning models and algorithms to address big data classification problems‎.‎ Existing machine learning techniques like the decision tree ‎(‎a hierarchical approach‎)‎‎,‎ random forest ‎(‎an ensemble hierarchical approach‎)‎‎,‎ and deep learning ‎(‎a layered approach‎)‎ are highly suitable for the system that can handle such problems‎.‎ This book helps readers‎,‎ especially students and newcomers to the field of big data and machine learning‎,‎ to gain a quick understanding of the techniques and technologies‎;‎ therefore‎,‎ the theory‎,‎ examples‎,‎ and programs ‎(‎Matlab and R‎)‎ presented in this book have been simplified‎,‎ hardcoded‎,‎ repeated‎,‎ or spaced for improvements‎.‎ They provide vehicles to test and understand the complicated concepts of various topics in the field‎.‎ It is expected that the readers adopt these programs to experiment with the examples‎,‎ and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems‎.‎ The presentation format of this boo‎.‎‎.‎‎.‎