# Understanding Support Vector Machine via Examples

In the previous post on Support Vector Machines (SVM), we looked at the mathematical details of the algorithm. In this post, I will be discussing the practical implementations of SVM for classification as well as regression. I will be using the iris dataset as an example for the classification problem, and a randomly generated data as an example for the regression problem.

# Switching to Hugo from Nikola

I have been using Nikola to build this Blog. Its a great static site build system that is based on Python. However, It has some crazy amount of dependencies (to have reasonable looking site). It uses restructured text (rst) as the primary language for content creation. Personally, I use markdown for almost every thing else - taking notes, making diary, code documentation etc. Furthermore, given Nikola tries to support almost everything in a static site builder, lately its is becoming more and more bloated.

# Descriptive Statistics

One of the first tasks involved in any data science project is to get to understand the data. This can be extremely beneficial for several reasons: Catch mistakes in data See patterns in data Find violations of statistical assumptions Generate hypotheses etc. We can think of this task as an exercise in summarization of the data. To summarize the main characteristics of the data, often two methods are used: numerical and graphical.

# My Arch Linux Setup with Plasma 5

UPDATE: Please see my latest post on installing Arch linux with Gnome 3 for an upto date version of this guide. Arch Linux is a general purpose GNU/Linux distribution that provides most up-to-date software by following the rolling-release model. Arch Linux allows you to use updated cutting-edge software and packages as soon as the developers released them. KDE Plasma 5 is the current generation of the desktop environment created by KDE primarily for Linux systems.

# Support Vector Machines

In this post we will explore a class of machine learning methods called Support Vector Machines also known commonly as SVM.

# Python Tutorial - Week 2

In the Week 1 we got started with Python. Now that we can interact with python, lets dig deeper into it.

This week we will go over some additional fundamental things common in any program - interactive input from users, adding comments to your code, use of conditional logic i.e. `if - else` conditions, loops, formatted output with strings and `print()` statements.

# EDA of Lending Club Data - II

In the last post we looked at some initial cleanup of the data. We will start from there by loading the pickled dataframe.