Analyze and understand your data with the power and simplicity of Python
About This Machine Learning with Open CV and Python Video course
- Prepare your data for analysis and use it to implement regression, clustering, and more
- Put to use the machine learning modules offered by OpenCV
- Build superior machine learning models with the help of OpenCV using this easy-to-follow course
Machine Learning with Open CV and Python In Detail
OpenCV is a library of programming functions mainly aimed at real-time computer vision. This video course will show you how machine learning is great choice to solve real-word computer vision problems and how you can use the OpenCV modules to implement the popular machine learning concepts.
The video will teach you how to work with the various OpenCV modules for statistical modelling and machine learning. You will start by preparing your data for analysis, learn about supervised and unsupervised learning, and see how to implement them with the help of real-world examples. The course will also show you how you can implement efficient models using the popular machine learning techniques such as classification, regression, decision trees, K-nearest neighbors, boosting, and neural networks with the aid of C++ and OpenCV.
Python, Data Science training table of contents (duration : 1h35m)
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Introduction to Machine Learning
- The Course Overview free 00:03:01
- The Basics of Machine Learning free 00:06:09
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Extracting Features and Preparing the Data
- Creating Training Data and Extracting Information 00:06:18
- Extracting Features 00:04:07
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Classifier and Regression
- K-Nearest Neighbors 00:08:37
- Logistic Regression 00:08:03
- Normal Bayes Classifier 00:04:27
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Decision Trees and Support Vector Machines
- Decision Trees 00:10:13
- Support Vector Machines 00:12:02
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Neural Networks
- Artificial Neural Networks 00:12:30
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Unsupervised Learning and Introduction to Deep Learning
- Unsupervised Learning 00:05:03
- Deep Learning 00:15:04
- Certificate
Instructor : Packt
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What is the required level to follow this tutorial ?intermediate
