1 Introduction to machine learning

“There are only patterns, patterns on top of patterns, patterns that affect other patterns. Patterns hidden by patterns. Patterns within patterns.” – Chuck Palahniuk

We love patterns. Be it our business or our life, we find patterns and (generally) tend to stick to them. We have our preferences of groceries we buy, telecom operators and calling packs we use, news articles we follow, movie genre and audio tracks we like – these all are examples of patterns of ours preferences. We love patterns, and more then patterns we love finding them, arranging them and may be getting used to them!

Then there is cliché going on -  “Data is the new electricity”. Data is indeed precious, nobody can deny that. But data in itself, in its purest form will be of no use. Until it is cleaned, arranged, analysed and visualised – we cannot develop any insights from it. We cannot find any patterns in it! Data sciences, machine learning and artificial intelligence are helping us in uncovering these patterns – so that we can take more insightful and balanced decisions in our activities and business.

1.1 Data, data types, data management and quality

1.1.1 What is Data

1.1.2 Various types of Data

1.1.3 Data quality

1.1.4 Data engineering and management

1.2 Data Analysis, Machine Learning, Artificial Intelligence and Business Intelligence

1.3 Nuts and bolts of Machine Learning

1.4 Types of Machine Learning algorithms

1.4.1 Supervised Learning

1.4.2 Unsupervised algorithms

1.4.3 Semi-supervised algorithms

1.4.4 Reinforcement learning

1.5 Technical toolkit

1.6 Summary