Best Online AI and Machine Learning Training Course in India by SkillXS IT Solutions

The term machine learning means to enable machines to think and learn without using any software. The goals of the machine-learning are to enable machines to do prediction, clustering, and make well-informed choices from a given dataset.
NOIDA, India - Sept. 25, 2020 - PRLog -- Owing to infinite applications in numerous fields, a career in machine learning will never disappoint you. It is a stable and lucrative career option that will provide money and balanced life. According to some reliable online website, the average salary of a machine learning engineer in India is approx. 7 lakhs per annum. The bright side is this would increase substantially with experience.

An entry-level Machine Learning Engineer with less than 1-year experience can expect to earn an average total compensation (includes tips, bonus, and overtime pay) of INR 501,571 based on 113 salaries. An early career Machine Learning Engineer with 1-4 years of experience earns an average total compensation of INR 693,442 based on 328 salaries. A mid-career Machine Learning Engineer with 5-9 years of experience earns an average total compensation of INR 1,159,032 based on 78 salaries. An experienced Machine Learning Engineer with 10-19 years of experience earns an average total compensation of INR 1,948,718 based on 19 salaries.

SkillXS IT Solutions
is the pioneer in the field of machine learning courses. It provides online and affordable machine learning courses that can take your career to the next level.

Course Summary:

The Machine Learning Specialist certification is for the candidates, who wants to learn algorithm coding and formula and other aspects of the data and analytics.  This Machine Learning Courses are the concoction of Data Science with R, Introduction to Machine Learning, Random Forest, General Boosting & Bagging, Support Vector Machines, Neural Networks and Text Mining with R.


• Develop an understanding of categorical variables and continuous variables, that helps in using the boosting and bagging methods effectively, understanding the NN algorithms work.
• Understand kernel functions such as: spline kernels, linear, radial basis function and polynomial and Text Mining with R are based on the intelligence of statistics and R.
• Explore R language fundamentals, including basic syntax, variables, and types

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