Machine Learning

Since the main task in machine learning is to select a model and train it on some data, the two things that can go wrong are 'bad model' and 'bad data'.

Introduction In this blog, we will be going over the below 6 main challenges of Machine Learning: Insufficient quantity of training data Non-representative training data Poor quality data Irrelevant Features Overfitting the training data Underfitting the training data Insufficient Quantity of Training Data To teach a toddler what a apple is, all it takes is for you to point to a apple and say “apple” or sometimes repeating this procedure a few times....

This blog introduces a lot of fundamental concepts (and jargons) that every data scientist should know by heart.

The first ML application that really became mainstream, improving the lives of hundereds of millions of people, took over the world back in 1990s: the spam filter. What is Machine Learning? Machine learning is the science (and art) of programming computers so they can learn from data. More general definition: [Machine learning is the] field of study that gives that ability to learn without being explicity programmed. – Arthur Samuel, 1959...