Machine learning using Python (level 2)


Machine Learning and Deep Learning are so persistent in today’s world that one may probably be using it more than 10 times a day without knowing it. Facebook tag suggestions is one of the very common example linked to it. One can think of Artificial Intelligence (AI), Machine Learning and Deep Learning as a set of items nested within each other. Deep Learning is a subset of Machine Learning and Machine Learning is a subset of AI which is simply the science and engineering of making intelligent machines. Machine Learning uses algorithms to analyse data, learn from the data, and then make informed decision accordingly. However, Deep learning structures algorithms in layers and high-level representations to create an ‘Artificial Neural Network’ that can learn, understand and make intelligent decisions. As the term specifies, Deep Learning is stimulated by the human brain and is based on ‘Artificial Neural Network’ which is developed on a similar architecture of human brain.

Course Outline:

Fundamentals of Machine Learning
Types of Machine leaning Algorithms
Planning of Machine Learning
Mathematical and Statistical Concepts- A Quick Recap Regression
Tree Modelling
Reinforcement Learning
Machine Learning with R
Deep Learning Going Deep Using TensorFlow
Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)
Distributed TensorFlow
Deep Learning Applications