About This Course
In this course, we will examine in detail the R software, which is the most popular statistical programming language of recent years.
You will start with exploring different learning methods, clustering, classification, model evaluation methods and performance metrics. From there, you will dive into the general structure of the clustering algorithms and develop applications in the R environment by using clustering and classification algorithms for real-life problems Next, you will learn to use general definitions about artificial neural networks, and the concept of deep learning will be introduced. The elements of deep learning neural networks, types of deep learning networks, frameworks used for deep learning applications will be addressed and applications will be done with R TensorFlow package. Finally, you will dive into developing machine learning applications with SparkR, and learn to make distributed jobs on SparkR.
- Certificate will provided in this course on Completion
- Full lifetime access
- Available on Mobile & Laptop
What Students Will Learn In Your Course?
- Classify data with the help of statistical methods such as k-NN Classification, Logistic Regression, and Decision Trees
- Deal with imbalanced datasets in artificial neural networks
- Deep learning algorithms Tensorflow background in R
- Write machine learning scripts with SparkR
Are There Any Course Requirements Or Prerequisites?
Experience in data analysis, business analysis, statistics.
Who Are Your Target Students?
This course is designed for data analysts, big data enthusiasts, business analysts, business intelligent specialists, statisticians, econometricians and for everyone interested in data analysis and data science
- 35 lectures