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.
Basic programming skills (in Python), algorithm design, basics of probability & statistics.
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.