An automated learning platform utilizes a brief basis for basic concepts in machine learning and common machine learning algorithms. We will summarize the most popular standards and supervised learning algorithms, including linear regression, introduction to Bayesian learning and Bayesian algorithm, support for vector machines, nuclei and neural networks, and many more with the Foundation for Deep Learning. We will also stamp the compiled basic algorithms. FRM (character reduction methods) will also be discussed during training. We will help students acquire basic concepts of computational learning theory. In our training course, there will be a discussion about the area of imposition, availability, bias, diversity, etc. The course will be implemented through practical problem-solving exercises with Python programming and some training sessions with the help of experienced colleges.
About The Course –
Learning to learn the automated world, however, is increasingly needed among professional firms who know the ins and outs of automated learning. The size of the automated learning market is expected to grow from $ 1.03 billion in 2016 to $ 8.81 billion by 2022, with a compound annual growth rate (CAGR) of 44.1% over the forecast period.
Learning Objectives –
- Controlling the concepts of learning under supervision and uncensored.
- Obtain a mastery of principles, algorithms and applications of automated learning through a practical approach that includes work on 28 final projects and projects.
- Gain accurate knowledge of the mathematical and instructional aspects of machine learning.
- Understand the concepts and operation of supporting vectors, SVM core, naive swords, tree resolution classification, random forest classification, logistic regression, and closest neighbors to K, K collection methods and more.
- Understanding theoretical concepts and how they relate to the practical aspects of machine learning.
- Be able to design a wide range of robust learning algorithms, including deep learning systems, assemblies and recommendations.
Summer Training | Summer Internship | Winter Training Program in Machine Learning :-
Summer Training Cum Summer Internship in Machine Learning:-
Winter Training in Machine Learning:-
- Lectures 0
- Quizzes 0
- Duration 50 hours
- Skill level All levels
- Language English
- Students 700
- Assessments Yes