Hands-On Machine Learning with Python
Packt Publishing Limited (Verlag)
978-1-83882-008-4 (ISBN)
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About This Book
* Extensive coverage on formulating the right questions about a given problem to help in model selection
* Taking students through techniques for data processing, manipulation, and transformation
* Providing practical methods for deploying models into production
Who This Book Is For
The reader of this course should have basic knowledge of the Python programming language. He/she must have knowledge of data types in Python, be able to write functions, and also have the ability to import and use libraries and packages in python. Familiarity with basic linear algebra, basic probability, and basic calculus is assumed although not required to fully complete this course.
What You Will Learn
* Use scikit-learn, pandas, numpy library to perform machine learning and data analysis tasks
* Obtain, verify, clean and transform data into a correct format for use
* Perform exploratory analysis and extract features from the data.
* Build models for regression, classification and clustering tasks.
* Evaluate the performance of a model with the right metric
* Deploy a final machine learning model into production
In Detail
This course gives students basic ideas behind machine learning methods as well as a deeper understanding of how and why they work. Emphasis is placed on how to get these algorithms to work in practice, rather than focusing on mathematical derivations. Through a project-based approach, the course gives students the opportunity to implement algorithms themselves and gain experience with them. The course covers various machine learning techniques for both supervised and unsupervised learning approaches. It also goes further to teach students about deploying a model into production.
Brent Kievit is currently the head of Google Image Search Metrics. He is a Ph.D. in cognitive science from Indiana University and is involved in multiple tech startups. His background is in natural language processing (NLP), big data, information visualization, and gamification. He has a lot of experience in web development, data analysis, and information visualization. Kiran Kumar is a Ph.D. candidate at Indiana University researching and developing statistical models to understand different aspects of human attention and decision making. His Master's degree in computer science and hands-on experience in software development for over 3 years has enabled him to create robust and efficient algorithms to interpret and analyze behavioral, image and textual data. He also has successfully published papers in reputed conferences and given talks to a large audience with diverse backgrounds. Ramya Rao has a Master's degree in Computer Science from Indiana University, where she also worked as a Research Assistant and developed a keen interest in Machine Learning, Computer Vision, Deep Learning and Data Analysis.Currently, as the Chief Science Officer in Brightlamp Inc, she delivers mobile applications which detects concussion through a video recording of an individual's eyes. Her primary focus is the identification and implementation of state-of-the-art research techniques to capture brain activity through the human visual system using videos of the eyes captured from mobile phones.
Erscheint lt. Verlag | 31.5.2019 |
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Verlagsort | Birmingham |
Sprache | englisch |
Maße | 191 x 235 mm |
Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
ISBN-10 | 1-83882-008-6 / 1838820086 |
ISBN-13 | 978-1-83882-008-4 / 9781838820084 |
Zustand | Neuware |
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