Python Machine Learning: Machine Learning and Deep
- 622 pages
- Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition 2, Sebastian Raschka, Vahid Mirjalili, eBook - Amazon.com
- Sebastian Raschka
- 07 March 2016 Sebastian Raschka
[PDF / EPUB] Python Machine Learning: Machine Learning and Deep Learning with Python, scikit–learn, and TensorFlow, 2nd Edition 2, Sebastian Raschka, Vahid Mirjalili, eBook – Amazon.com I bought the first version of this book and now also the second The new version is very comprehensive If you are using Python it s almost a reference I also like the emphasis on neural networks and Te Learning: Machine PDF ↠ I bought the first version of this book and now also the second The new version is very comprehensive If you are using Python it s almost a reference I also like the emphasis on neural networks and TensorFlow which Python Machine eBook Ì in Machine Learning: Machine Learning and MOBI :ß my view is where the Python community is headingI am also planning to use this book in my teaching at Oxford University The data pre processing sections are also good I found the seuence flow slightly unusual but for an expert level audience it s not a major issueAjit Jaokar Data Science for IoT Course Creator and Lead Tutor at the University of Oxford Principal Data ScientistSebastian Raschka author of the bestselling book Python Machine Learning has many years of experience Machine Learning: Machine Learning and MOBI :ß with coding in Python and he has given several seminars on the practical applications of data science machine learning and deep learning including a machine learning tutorial at SciPy the leading conference for scientific computing in PythonWhile Sebastian s academic research projects are mainly centered around problem solving in computational biology he loves to write and talk about data science machine learning and Python in general and he is motivated to help people develop data driven solutions without necessarily reuiring a machine learning backgroundHis work and contributions have recently been recognized by the departmental outstanding graduate student award as well as the ACM Computing Reviews Best of award In his free time Sebastian loves to contribute to open source projects and the methods that he has implemented are now successfully used in machine learning competitions such as KaggleVahid Mirjalili obtained his PhD in mechanical engineering working on novel methods for large scale computational simulations of molecular structures Currently he is focusing his research efforts on applications of machine learning in various computer vision projects at the Department of Computer Science and Engineering at Michigan State UniversityVahid picked Python as his number one choice of programming language and throughout his academic and research career he has gained tremendous experience with coding in Python He taught Python programming to the engineering class at Michigan State University which gave him a chance to help students understand different data structures and develop efficient code in PythonWhile Vahid s broad research interests focus on deep learning and computer vision applications he is especially interested in leveraging deep learning techniues to extend privacy in biometric data such as face images so that information is not revealed beyond what users intend to reveal Further he also collaborates with a team of engineers working on self driving cars where he designs neural network models for the fusion of multispectral images for pedestrian detection.