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Bitcoin Price

Modeling Bitcoin’s Market Capitalization

  • Post published:July 25, 2017
  • Post category:Machine Learning/Predictive Analysis/Scikit-learn
  • Post comments:0 Comments
  • Reading time:7 mins read

Bitcoin has been in news quite a bit lately with the price soaring. It was named the top performing currency four of the last five year. And it’ price has the…

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countvectorizer sklearn example

Countvectorizer sklearn example

  • Post published:May 23, 2017
  • Post category:Data Analysis/Machine Learning/Scikit-learn
  • Post comments:5 Comments
  • Reading time:53 mins read

This countvectorizer sklearn example is from Pycon Dublin 2016. For further information please visit this link. The dataset is from UCI. In [2]: messages = [line.rstrip() for line in open('smsspamcollection/SMSSpamCollection')] In [3]: print (len(messages))…

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Principal Component Analysis in scikit-learn

Principal Component Analysis in scikit-learn

  • Post published:August 1, 2016
  • Post category:Machine Learning/Scikit-learn
  • Post comments:0 Comments
  • Reading time:78 mins read

Principal Component Analysis (PCA) is an orthogonal linear transformation that turns a set of possibly correlated variables into a new set of variables that are as uncorrelated as possible. The…

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Naiive Bayes in scikit-learn

  • Post published:July 31, 2016
  • Post category:Machine Learning/Scikit-learn
  • Post comments:1 Comment
  • Reading time:28 mins read

Naïve Bayes is a simple but powerful classifier based on a probabilistic model derived from the Bayes' theorem. Basically it determines the probability that an instance belongs to a class…

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Decision Trees in scikit-learn

Decision Trees in scikit-learn

  • Post published:July 31, 2016
  • Post category:Machine Learning/Scikit-learn
  • Post comments:10 Comments
  • Reading time:37 mins read

Decision trees are very simple yet powerful supervised learning methods, which constructs a decision tree model, which will be used to make predictions. The main advantage of this model is…

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Support Vector Machine in scikit-learn

Support Vector Machine in scikit-learn

  • Post published:July 31, 2016
  • Post category:Machine Learning/Scikit-learn
  • Post comments:0 Comments
  • Reading time:92 mins read

Support Vector Machines has become one of the state-of-the-art machine learning models for many tasks with excellent results in many practical applications. One of the greatest advantages of Support Vector…

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Regression in scikit-learn

Regression in scikit-learn

  • Post published:July 31, 2016
  • Post category:Machine Learning/Scikit-learn
  • Post comments:0 Comments
  • Reading time:89 mins read

We will compare several regression methods by using the same dataset. We will try to predict the price of a house as a function of its attributes. In [6]: import numpy…

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kNN

k-Nearest Neighbors(kNN)

  • Post published:July 30, 2016
  • Post category:Machine Learning
  • Post comments:2 Comments
  • Reading time:100 mins read

k-Nearest Neighbors(kNN) Pros: High accuracy, insensitive to outliers, no assumptions about data Cons: Computationally expensive, requires a lot of memory Works with: Numeric values, nominal values We have an existing…

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