pilot617

activeadmin

The administration framework for Ruby on Rails applications.

Handwritten-Digit-Recognition-using-CNN

ml19-20w

CS 771A: Introduction to Machine Learning, IIT Kanpur, 2019-20-winter offering

Titanic-Machine-Learning-from-Disaster

The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we are asked to complete the analysis of what sorts of people were likely to survive. In particular, we are asked to apply the tools of machine learning to predict which passengers survived the tragedy.

ultimate-angular-starter-seed

The starter project for the "Ultimate Angular 1.x Fundamentals" course

pilot617/activeadmin

The administration framework for Ruby on Rails applications.

pilot617/Handwritten-Digit-Recognition-using-CNN

pilot617/ml19-20w

CS 771A: Introduction to Machine Learning, IIT Kanpur, 2019-20-winter offering

pilot617/Titanic-Machine-Learning-from-Disaster

The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we are asked to complete the analysis of what sorts of people were likely to survive. In particular, we are asked to apply the tools of machine learning to predict which passengers survived the tragedy.

pilot617/ultimate-angular-starter-seed

The starter project for the "Ultimate Angular 1.x Fundamentals" course