Advanced Data Mining projects with R (2017)

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 243.6 MB
  • Uploaded By freezedude
  • Downloads 731
  • Last checked 3 days ago
  • Date uploaded 9 years ago
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Infohash : 50A50DEACA61DD47E177201C64356DB1ABA4A02D



Advanced Data Mining projects with R (2017)



Details:



Advanced Data Mining projects with R
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 243 MB
Genre: eLearning | Language: English


Advanced Data Mining Projects with R takes you one step ahead in understanding the most complex data mining algorithms and implementing them in the popular R language. Follow up to our course Data Mining Projects in R, this course will teach you how to build your own recommendation engine. You will also implement dimensionality reduction and use it to build a real-world project. Going ahead, you will be introduced to the concept of neural networks and learn how to apply them for predictions, classifications, and forecasting. Finally, you will implement ggplot2, plotly and aspects of geomapping to create your own data visualization projects.By the end of this course, you will be well-versed with all the advanced data mining techniques and how to implement them using R, in any real-world scenario.

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Files:

Advanced Data Mining projects with R (2017) 1 Clustering with E-commerce Data
  • Clustering Methods – K means and Hierarchical.mp4 (58.1 MB)
  • Clustering Methods – Model Based, Other and Comparison.mp4 (20.3 MB)
  • The Course Overview.mp4 (13.5 MB)
  • Understanding Customer Segmentation.mp4 (6.6 MB)
2 Building a Retail Recommendation Engine
  • Application of Methods and Limitations of Collaborative Filtering.mp4 (4.6 MB)
  • Practical Project.mp4 (17.4 MB)
  • What Is Recommendation-.mp4 (12.9 MB)
3 Dimensionality Reduction
  • Parametric Approach to Dimension Reduction.mp4 (4.9 MB)
  • Practical Project around Dimensionality Reduction.mp4 (47.4 MB)
  • Why Dimensionality Reduction-.mp4 (15.0 MB)
4 Applying Neural Network to Healthcare Data
  • Introduction to Neural Networks.mp4 (7.3 MB)
  • Merits and Demerits of Neural Networks.mp4 (3.8 MB)
  • Neural Network Implementation in R.mp4 (5.3 MB)
  • Neural Networks for Classification.mp4 (5.9 MB)
  • Neural Networks for Forecasting.mp4 (4.7 MB)
  • Neural Networks for Prediction.mp4 (12.8 MB)
  • Understanding the Math Behind the Neural Network.mp4 (3.1 MB)

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