Data Science in R: Regression & Classification Analysis
Master Complete Hands-On Regression Analysis & Classification for applied Statistical Modelling & Machine Learning in R
Ratings 4.06 / 5.00
What You Will Learn!
- Your comprehensive guide to Regression Analysis & Classification for machine learning using R-programming language
- It covers theory and applications of supervised machine learning with the focus on regression & classification analysis
- Implement Machine Learning Techniques/Classification Such As Random Forests, SVM etc in R
- Build machine learning based regression & classification models and test their robustness in R
- Perform model's variable selection and assess regression model's accuracy
- Evaluate Model Performance & Learn The Best Practices For Evaluating Machine Learning Model Accuracy
- Compare different different machine learning models in R
- Learn R-programming from scratch: R crash course is included that you could start R-programming for machine learning
- Graphically representing data in R before and after analysis
Description
Master Regression Analysis and Classification in R: Elevate Your Machine Learning Skills
Welcome to this comprehensive course on Regression Analysis and Classification for Machine Learning and Data Science in R. Get ready to delve into the world of supervised machine learning, specifically focusing on regression analysis and classification using the R-programming language.
What Sets This Course Apart:
Unlike other courses, this one not only provides guided demonstrations of R-scripts but also delves deep into the theoretical background. You'll gain a profound understanding of Regression Analysis and Classification (Linear Regression, Random Forest, KNN, and more) in R. We'll explore various R packages, including the caret package, for supervised machine learning tasks.
This course covers the essential aspects of practical data science, particularly Machine Learning related to regression analysis. By enrolling in this course, you'll save valuable time and resources typically spent on expensive materials related to R-based Data Science and Machine Learning.
Course Highlights:
8 Comprehensive Sections Covering Theory and Practice:
Gain a thorough understanding of supervised Machine Learning for Regression Analysis and classification tasks.
Apply parametric and non-parametric regression and classification methods effectively in R.
Learn how to correctly implement and test regression and classification models in R.
Master the art of selecting the best machine-learning model for your specific task.
Engage in coding exercises and an independent project assignment.
Acquire essential R-programming skills.
Access all scripts used throughout the course, facilitating your learning journey.
No Prerequisites Needed:
Even if you have no prior experience with R, statistics, or machine learning, this course is designed to be your complete guide. You will start with the fundamental concepts of Machine Learning and R-programming, gradually building up your skills. The course employs hands-on methods and real-world data, ensuring a smooth learning curve.
Practical Learning and Implementable Solutions:
This course is distinct from other training resources. Each lecture is structured to enhance your Regression modeling and Machine Learning skills, offering a clear and easy-to-follow path to practical implementation. You'll gain the ability to analyze diverse data streams for your projects, enhancing your value to future employers with your advanced machine-learning skills and knowledge of cutting-edge data science methods.
Ideal for Professionals:
This course is tailored for professionals who need to leverage cluster analysis, unsupervised machine learning, and R in their field.
Hands-On Exercises:
The course includes practical exercises, offering precise instructions and datasets for running Machine Learning algorithms using R tools.
Join This Course Today:
Seize the opportunity to become a master of Regression Analysis and Classification in R. Enroll now and unlock the potential of your Machine Learning and Data Science skills!
Who Should Attend!
- The course is ideal for professionals who need to use cluster analysis, unsupervised machine learning and R in their field.
- Everyone who would like to learn Data Science Applications in the R & R Studio Environment
- Everyone who would like to learn theory and implementation of Machine Learning On Real-World Data
