Advanced Machine Learning with R MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 358 MB Genre: eLearning | Language: English
Machine learning is the subfield of computer science that gives computers the ability to learn without being explicitly programmed. It explores the study and construction of algorithms that can learn from and make predictions on data. The R language is widely used among statisticians and data miners to develop statistical software and data analysis. Machine Learning is a cross-functional domain that uses concepts from statistics, math, software engineering, and more. In this course, you値l get to know the advanced techniques for Machine Learning with R, such as hyper-parameter turning, deep learning, and putting your models into production through solid, real-world examples. In the first example, you値l learn all about neural networks through an example of DNA classification data. You値l explore networks, implement them, and classify them. After that, you値l see how to tune hyper-parameters using a data set of sonar data and you値l get to know their properties. Next, you値l understand unsupervised learning with an example of clustering politicians, where you値l explore new patterns, understand unsupervised learning, and visualize and cluster the data. Moving on, we discuss some of the details of putting a model into a production system so you can use it as a part of a larger application. Finally, we値l offer some suggestions for those who wish to practice the concepts further.