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Machine Learning

Coding FP-growth algorithm in Python 3

FP-growth algorithm Have you ever gone to a search engine, typed in a word or part of a word, and the search engine automatically completed the search term for you? Perhaps it recommended something you didn’t even know existed, and you searched for that instead. This requires a way to find frequent itemsets efficiently. FP-growth […]

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Machine Learning

AdaBoost (Python 3)

AdaBoost The AdaBoost (adaptive boosting) algorithm was proposed in 1995 by Yoav Freund and Robert Shapire as a general method for generating a strong classifier out of a set of weak classifiers . AdaBoost works even when the classifiers come from a continuum of potential classifiers (such as neural networks, linear discriminants, etc.) AdaBoost Pros: […]

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Machine Learning

Apriori Algorithm (Python 3.0)

Apriori Algorithm The Apriori algorithm principle says that if an itemset is frequent, then all of its subsets are frequent.this means that if {0,1} is frequent, then {0} and {1} have to be frequent. The rule turned around says that if an itemset is infrequent, then its supersets are also infrequent. We first need to […]

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Kaggle

Kaggle Tutorial using Kobe Bryant Dataset – Part 2

This part is a tutorial using Kobe Bryant Dataset – Part 2. The dataset is from Kaggle and the comprehensive post is divided into multiple parts. This is continued from part -1 . The following presents a thought process of creating and debugging ML algorithm for predicting whether a shot is successfull or missed (binary classification […]

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Kaggle

Kaggle Tutorial using Kobe Bryant Dataset – Part 1

This part is a kaggle tutorial using Kobe Bryant Dataset – Part 1. You can get the data from https://www.kaggle.com/c/kobe-bryant-shot-selection . What excited me was that this dataset is excellent to practice classification basics, feature engineering, and time series analysis. Importing Data Let us start with importing the basic libraries we need and the data […]

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Machine Learning

Machine learning applications in Government and Education

Described below are some of the examples of machine learning applications in education and government. Machine learning applications in Government and Education Education Machine learning provides new opportunities to tackle the challenge of large-scale grading automatically by analyzing data generated while students interact with teachers and other students.  Data mining and predictive analysis are applied […]

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Machine Learning

Machine Learning applications in Tertiary Sector-part 2

This blog is a continuation of the last blog post regarding machine learning applications in tertiary sector of the economy. Detailed below are some more machine learning applications in Tertiary Sector. Hotel and Tourism Artificial neural networks, Gaussian process regression and support vector machines are the most widely used machine learning methods for forecasting in […]

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Machine Learning

Machine Learning applications in Tertiary Sector-part 1

Tertiary Sector is the service industry in an economy of a nation. It the largest sector in the western world and is growing at a rapid pace. It involves people interacting with other people and serving customers not transforming physical goods.This blog includes machine learning applications in Tertiary Sector. Described below are some of the […]