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Your search keyword 'LN cat08778a' showing total 5 results
Start Over LN cat08778a Publication Type Videos Publication Type Non-Print Resources
5 results on 'LN cat08778a'

1. Hands-on supervised machine learning with Python. [electronic resource]

Subjects
Python (Computer program language), Machine learning, Instructional films
Abstract

Summary: Teach your machine to think for itself! About This Video: Take a deep dive into supervised learning and grasp how a machine "learns" from data. Follow detailed and thorough coding examples to implement popular machine learning algorithms from scratch, developing a deep understanding along the way. Work your Python muscle! This course will help you grow as a developer by heavily relying on some of the most popular scientific and mathematical libraries in the Python language. In Detail: Supervised machine learning is used in a wide range of industries across sectors such as finance, online advertising, and analytics, and it's here to stay. Supervised learning allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more, while allowing the system to self-adjust and make decisions on its own. This makes it crucial to know how a machine "learns" under the hood.This course will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You'll embark on this journey with a quick course overview and see how supervised machine learning differs from unsupervised learning. Next, we'll explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you'll wrap up with a brief foray into neural networks and transfer learning. By the end of the video course, you'll be equipped with hands-on techniques to gain the practical know-how needed to quickly and powerfully apply these algorithms to new problems. All the codes of the course are uploaded on GitHub.

Published
2018

2. $#*! my dad says.

Subjects
Situation comedies (Television programs), Fiction television programs
Abstract

Summary: "Bonnie tries to start a family tradition. Henry gets in trouble for taking the blame for a friend's mistake. Ed makes a friend at the hospital with his personality"--Wikipedia WWW site, viewed June 9, 2014.

Published
2010

3. Soft cinema : navigating the database.

Subjects
Nonfiction films
Abstract

Summary: "DVD version of an art installation of three films created with the use of image databases, in which the contents of each film are drawn from a unique database programmed to display a different sequence of video clips and screen layouts at each viewing. Includes interview with Lev Manovich ; database visualization ; documentation of Soft Cinema installations ; architectural designs for Soft Cinema"--videodisc container.

Published
2005

4. A bout de souffle.

Author

Fotiade, Ramona

Subjects
Interpretation--French films, French cinema
Published
1960

5. Emerging paradigms in machine learnin.

Author

Ramanna, Sheela, Jain, L. C., and Howlett, Robert J.

Subjects
Artificial Intelligence, Machine Learning, Artificial Neural Networks
Abstract

Subject: This book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The multidisciplinary nature of machine learning makes it a very fascinating and popular area for research. The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems. Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary data streams are a key part of this book.

Published
1945

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