Online data science courses to jumpstart your future.
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Commonly used in Machine Learning, Naive Bayes is a collection of classification algorithms based on Bayes Theorem. It is not a single algorithm but a family of algorithms that all share a common principle, that every feature being classified is independent of the value of any other feature.
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In this post, we are going to introduce you to the Support Vector Machine (SVM) machine learning algorithm. We will follow a similar process to our recent post Naive Bayes for Dummies; A Simple Explanation by keeping it short and not overly-technical. The aim is to give those of you who are new to machine learning a basic understanding of the key concepts of this algorithm.
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Learn how to build a React app with User Authentication
This post will show you how to build a React application from scratch, using the Stormpath React SDK to add features that allow people to sign up, login, and even view their own user profile.
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This React.js tutorial will teach you how to create a simple todo application using React JS and the Flux architecture. React JS is making some waves in the community recently due to its alleged performance increases over other heavy favourites (like Angular JS), especially when it comes to writing out lists.
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If you use Docker, you very quickly run into a common question: how do you make Docker work across multiple hosts, datacenters, and different clouds. One of the simplest solutions is Docker Swarm. Docker summarizes it best as “a native clustering for Docker…[which] allows you create and access to a pool of Docker hosts using the full suite of Docker tools.”
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DataCamp's Into to R training course teaches you how to use R programming for data science at your own pace with video tutorials & interactive challenges.
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Google Analtyics goals are essential if you want to track and improve your conversions. Learn how to set these up step by step and improve your conversions.
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Here is a complete tutorial on the regularization techniques of ridge and lasso regression to prevent overfitting in prediction in python

Ridge and Lasso regression are powerful techniques generally used for creating parsimonious models in presence of a ‘large’ number of features. Here ‘large’ can typically mean either of two things:

Large enough to enhance the tendency of a model to overfit (as low as 10 variables might cause overfitting)
Large enough to cause computational challenges. With modern systems, this situation might arise in case of millions or billions of features
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A comprehensive learning path to become a data scientist using Python. Topics include machine learning, deep learning & pandas on Python.
The aim of this page is to provide a comprehensive learning path to people new to python for data analysis. This path provides a comprehensive overview of steps you need to learn to use Python for data analysis.
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These Python tutorials is suitable for programmers who have prior experience in other programming languages or basic knowledge of python programming.
What is TutLinks?

TutLinks.com is a tutorial links collection site. On TutLinks.com users can find any kind of tutorial be it a dance tutorial or cooking recipe or any technology you want to learn. Registered users can also submit their content (video, audio, blog) related to any tutorials or how to articles.

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