Amin Zollanvari is an Associate Professor of Electrical and Computer Engineering and the Head of Data Science Laboratory at Nazarbayev University. He received his B.Sc. and M.Sc. degrees in electrical engineering from Shiraz University, Iran, in 2003 and 2006, respectively, and a Ph.D. in electrical engineering from Texas A&M University, in 2010. He held a postdoctoral position at Harvard Medical School and Brigham and Women's Hospital, Boston MA (2010-2012), and later joined the Department of Statistics at Texas A&M University as an Assistant Research Scientist (2012-2014). He has taught a number of courses on machine learning, programming, and statistical signal processing both at graduate and undergraduate level and has authored over 80 research papers in prestigious journals and international conferences on fundamental and practical machine learning and pattern recognition. He is currently an IEEE Senior member and has served as an Associate Editor of IEEE Access since 2018.
Preface.
About This Book.
1. Introduction.
2. Getting Started with Python.
3. Three Fundamental Python Packages.
4. Supervised Learning in Practice: The First Application Using Scikit
Learn.
5. K
Nearest Neighbors.
6. Linear Models.
7. Decision Trees.
8. Ensemble Learning.
9. Model Evaluation and Selection.
10. Feature Selection.
11. Assembling Various Learning Stages.
12. Clustering.
13. Deep Learning with Keras
TensorFlow.
14. Convolutional Neural Networks.
15. Recurrent Neural Networks.
References.
Preface.- About This Book.- 1. Introduction.- 2. Getting Started with Python.- 3. Three Fundamental Python Packages.- 4. Supervised Learning in Practice: The First Application Using Scikit-Learn. - 5. K-Nearest Neighbors.- 6. Linear Models.- 7. Decision Trees.- 8. Ensemble Learning.- 9. Model Evaluation and Selection.- 10. Feature Selection.- 11. Assembling Various Learning Stages.- 12. Clustering.- 13. Deep Learning with Keras-TensorFlow. - 14. Convolutional Neural Networks.- 15. Recurrent Neural Networks.- References.
