This 30-part course consists of tutorials, quizzes, hands-on assignments and real-world projects to learn data science, as well as advanced python tools for data science. You can think of this list as a "Free Online Nano Book".
Most of the tutorials are self sufficient. But you should have some knowledge of Python to understand some project based tutorials like Predicting Titanic Survivors with Machine Learning.
Hi Somto, this is a good place to begin learning Data Science :)
It depends on your need. For example if you want to use cutting edge statistical methods , R is a better options while Python is better when you want to build a scalable product. These articles will help you understand it better:
Hello Shaurya, you can use the notebook along the tutorial. The best way to learn is by doing. Play with the note book, learn what those code is doing from the tutorial , post questions if you find any portion difficult to follow. In that way you will get best out of this tutorial :)
Feature bucketing is a feature engineering technique in which we convert continuous values of some feature ( for example age) to fixed ranges ( like 10-15, 15-20). This technique proves helpful in reducing noise endured by machine learning algorithms resulting in enhanced performance. You can explore the idea further in this blog :
Creating Buckets or Clusters for Numeric Column Values in Exploratory
Data Scientist. Public Speaker. Consultant. Astrophysicist. Space Scientist.
Big Data & Data Science advisor, TedX speaker, c...
Hello Kirk, which area of research do you think needs immediate attention for advancement of machine learning/ data science?
On 15 April, 1912 Titanic met with an unfortunate event - it collided with an iceberg and sank. The ship was carrying 2224 people and that tragic accident costed the life of 1502 passengers.
In this tutorial we will be predicting which passenger survived the accident and who couldn't from different features like age, sex, class, etc. This problem is hosted by Kaggle as a challenge...
