Machine Learning Made Easy : Beginner to Advanced using R

Machine Learning Made Easy : Beginner to Advanced using R, available at $54.99, has an average rating of 4.58, with 129 lectures, 11 quizzes, based on 103 reviews, and has 4396 subscribers.

You will learn about R Programming, Data Handling and Cleaning, Basic Statistics, Classical Machine Learning Algorithms, Model Selection and Validation, Advanced Machine Learning Algorithms, Ensemble Learning. Write your own R scripts and work in R environment. Import, manipulate, clean up, sanitize and export datasets. Understand basic statistics and implement using R. Understand data science life cycle while understanding steps of building, validating, improving and implementing the machine learning models. Do powerful analysis on data, find insights and present them in visual manner. Learn classical algorithms like Linear Regression, Logistic Regression, Decision Trees and advance machine learning algorithms like SVM, Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and clustering algorithms like K-means. Know how each machine learning algorithm works and which one to choose according to the type of problem. Build more than one powerful machine learning model and be able to select the best one and improve it further. This course is ideal for individuals who are Anyone interested in Data Science and Machine Learning. or Students who want a head start in Data Science field. or Data analysts who want to upgrade their skills in Machine Learning. or People who want to add value to their work and business by using Machine Learning. or People with basics understanding of classical machine learning algorithms like linear regression or logistic regression, but want to learn more about it. or People interested in understanding application of machine learning algorithms on real business problems. or People interested in understanding how a machine learning algorithm works and what's the math behind it. It is particularly useful for Anyone interested in Data Science and Machine Learning. or Students who want a head start in Data Science field. or Data analysts who want to upgrade their skills in Machine Learning. or People who want to add value to their work and business by using Machine Learning. or People with basics understanding of classical machine learning algorithms like linear regression or logistic regression, but want to learn more about it. or People interested in understanding application of machine learning algorithms on real business problems. or People interested in understanding how a machine learning algorithm works and what's the math behind it.

Enroll now: Machine Learning Made Easy : Beginner to Advanced using R

Summary

Title: Machine Learning Made Easy : Beginner to Advanced using R

Price: $54.99

Average Rating: 4.58

Number of Lectures: 129

Number of Quizzes: 11

Number of Published Lectures: 129

Number of Published Quizzes: 11

Number of Curriculum Items: 140

Number of Published Curriculum Objects: 140

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

• R Programming, Data Handling and Cleaning, Basic Statistics, Classical Machine Learning Algorithms, Model Selection and Validation, Advanced Machine Learning Algorithms, Ensemble Learning.
• Write your own R scripts and work in R environment.
• Import, manipulate, clean up, sanitize and export datasets.
• Understand basic statistics and implement using R.
• Understand data science life cycle while understanding steps of building, validating, improving and implementing the machine learning models.
• Do powerful analysis on data, find insights and present them in visual manner.
• Learn classical algorithms like Linear Regression, Logistic Regression, Decision Trees and advance machine learning algorithms like SVM, Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and clustering algorithms like K-means.
• Know how each machine learning algorithm works and which one to choose according to the type of problem.
• Build more than one powerful machine learning model and be able to select the best one and improve it further.

Who Should Attend

• Anyone interested in Data Science and Machine Learning.
• Students who want a head start in Data Science field.
• Data analysts who want to upgrade their skills in Machine Learning.
• People who want to add value to their work and business by using Machine Learning.
• People with basics understanding of classical machine learning algorithms like linear regression or logistic regression, but want to learn more about it.
• People interested in understanding application of machine learning algorithms on real business problems.
• People interested in understanding how a machine learning algorithm works and what's the math behind it.

Target Audiences

• Anyone interested in Data Science and Machine Learning.
• Students who want a head start in Data Science field.
• Data analysts who want to upgrade their skills in Machine Learning.
• People who want to add value to their work and business by using Machine Learning.
• People with basics understanding of classical machine learning algorithms like linear regression or logistic regression, but want to learn more about it.
• People interested in understanding application of machine learning algorithms on real business problems.
• People interested in understanding how a machine learning algorithm works and what's the math behind it.