- Linear Algebra, Gradient Descent Algorithm in machine learning
Gradient Descent is one of the basic iterative optimization algorithms used in Machine Learning, and its deep-rooted in linear algebra and math.
It is the first algorithm explained by Andrew Ng course of Machine Learning.
If you are like me, lost in the math when Andrew explained it, you will find this post useful.
read more ...Using Scikit-learn's Naive BayesSpam Detector using Python
We will write a python code that detect spam using Naive Bayes Classifier.
read more ...Naive Bayes Classifier
Naive Bayes Classifier is one of the well known classifiers in supervised learning. I am going to show how it is calculated from a training data.
read more ...Scrubbing Natural Language Text Data
Scrubbing a natural language text data is a widely used process that has well defined steps which you will find it in many places. From Lucene which is the Full text search engine that is used in Elastic Search and Azure Search, to any data science project that is processing Natural Language, including different ML projects, and general search projects.
read more ...Naive Bayes by examples
Bayes and Naive Bayes are very important techniques in machine learning. I am going to cover the Naive Bayes Classifier which is widley used in machine learning, but before that I will explain in this post the Bayes’ theorm by examples
read more ...Detect Spam with Naive Bayes
Bayes and Naive Bayes are very important techniques in machine learning. I am going to cover and dig into Naive Bayes in machine learning, and practice that using Python to detect email span. I am going to split this into many posts, because I am going to cover theory and practice.
read more ...Descriptive statistics with Python Numpy.
Python libraries SciPy and Pandas already have off-the-shelf tools to calculate descriptive statistics, but behind the scene they are calling Numpy functionalities.
This post just to learn more Numpy, and its great arsenal of dealing with data.
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