Configure Celery to run as Daemon service

I am writing this post after consolidating my today’s deep search on How to configure celery to run as a Daemon?. I found many articles on the internet which are not enough and clear. After going through all the steps finally, I planned to write a blog which will have complete step-by-step procedure to make celery worker run as a Daemon.

Principal Component Analysis in Machine Learning

The definition of Principle Component Analysis(PCA) is Systematized way to transform input features into Principal components. The Principal components are used as new features. PCs are directions in data that maximize variance(obviously minimize information loss) when we Project/Compress down onto them. More variance of data along a PC, higher that PC is ranked. 

Outliers in Regression

As we saw the Regression is one of the popular machine learning algorithms, I have come over errors and performance of the regression in my previous blog. Outliers are causing in the regression that could also happen like the one in Support Vector Machines or in the Naive Bayes Classifier algorithm do. An outlier is the point of a data that is far away from the regression line. But I had a question that, is it necessary to remove the outliers and do the fit again? The answer is here.

Regression in Machine Learning

I have just started the Lesson 7 in Introduction to Machine Learning Udacity Course, the Regression. Linear Regression is one of the Continuous Supervised Learning methods in machine learning. In other words, it is used to predict the dependent variable(Y) based on values of independent variables(X). It can be used for the cases where we want to predict some continuous quantity like predicting the traffic in a Mall, Dwell time(Time spent in the same position, area, stages of a process).

Parameters in Support Vector Machines

Hey! I hope My Blog posts replicates the way I am going through the Machine Learning Course with Udacity. At the middle of Support Vector Machine‘s, I switched over to the next lesson on decision tree. Parameters available are  Kernel, C and Gamma. C parameter controls trade-off between Smooth decision boundary and classifying training points correctly. 

Decision Trees in Machine Learning

Decision trees are the yet another popular algorithm used in Machine Learning for making decisions and it is popular too. It Performs certain recursive actions before it comes at the end result, while plotting the same as visual it looks like a tree, hence called Decision Tree. As much like the Support Vector Machines and Naive Bayes Gaussian Algorithm, decision trees are also helpful in building Classification and Regression models.

Kernelized Support Vector Machines

In most of the cases of Supervised Learning Methods, while classification the output will not be linear. Linear Support Vector Machines (SVM’s), worked well for simple kinds of classification problems where the classes linearly separable or close to linearly separable.

Support Vector Machines

SVM’s are a set of supervised Learning methods used for, SVM’s are a set of supervised Learning methods used for,

(i) Classification,

(ii) Regression and

(iii) Outliers detection

Special Variables in Python and Inheritance

This special variable is to get the Doc String used in any any class of function. Now Consider this turtle.Turtle.__doc__ will return the Documentation of the Class Turtle. To use the __doc__ in Movie Class we created earlier

Google Style Guide for python

We do have our own Way of Writing Codes. In order to have the standardness in Code, to make our code clean and to follow the Python Code Style which is used widely commonly, it is essential for us to Follow the Google Style Style for Python. Here are some useful guides which I read and consolidated from here.