Machine Learning


Introduction to Machine learning


Some of the hottest words in today's technical world are Artificial Intelligence, Machine Learning, Neural Networks... They deserve to be! Machine learning has started touching our lives in every way and it will soon change almost every aspect of our life. The blogs below start with the most basic elementary concepts and move on to deeper aspects of the subject. They will move along as I continue to learn the subject.

Introduction

These blogs give an overview of what is AI, covering all these aspects and much more. I have made all attempts to stay away from all technical jargon.
This was an executive overview of the basic concepts. Other blogs below go deeper into a detailed understanding of various specific design and implementation aspects.

Fundamental Concepts

These blogs give you a very basic idea about what these terms mean. There is a very little technical content out here. More of basic concepts for someone who has no idea about the subject.
These are the basic concepts that power the various aspects of machine learning. It is very important to understand them conceptually. Once we have a good grasp of these topics, we can move a step forward into the deeper aspects.

Implementation

It is very important to have a good grasp of the concepts. But mere concepts are not enough. In fact they are meaningless until we have working code that does the job. After covering the concepts, the following blogs give a feel of how the things are implemented in code. Starting with the basic raw implementation of the algorithm, they proceed to give an introduction to the various open source libraries that make the task simple. Most of Machine learning code is implemented in Python. Some like R. Now, we also have JavaScript libraries to work on it. In spite of all that, Python remains the language of choice.
Python 3 is the version of choice. Most of these libraries have depricated or have announced deprication of Python 2.