Mahesha Godekere
/
Recent content on Mahesha GodekereHugo -- gohugo.ioen-usSun, 04 Mar 2018 00:00:00 +0000Central Tendency
/notes/central.tendency/
Sun, 04 Mar 2018 00:00:00 +0000/notes/central.tendency/Central tendency is "the statistical measure that identifies a single value as representative of an entire distribution". It aims to provide an accurate description of the entire dataset. It is the single value that is most representative of the dataset.
The mean, median and mode are the three commonly used measures of central tendency.
Mode: is a value/range that occurred with the highest frequency. Median: is the number that lies in the middle of a list of ordered numbers.Distributions
/notes/distributions/
Sun, 04 Mar 2018 00:00:00 +0000/notes/distributions/Observing the distribution and their characteristics have particular importance in statistics. Distributions describes
the data central tendency behaviour dispersion identify clusters, peaks and gaps Normal Distribution The normal distribution, also known as the Gaussian or standard normal distribution, is the distribution that all of its values in a symmetrical fashion, and most of the results are situated around the distribution mean.
Normally distribution is perfectly symmetric around its mean.IPynb Test
/notes/a.test/
Sun, 04 Mar 2018 00:00:00 +0000/notes/a.test/1: Linear regression - Introduction¶ A simple linear function¶To understand Machine Learning concepts , consider a simple linear function of x as below:
$ y = f(x) $ (1) ... simple linear function
$ x $ = Input variable / Feature $ y $ = Output variable / Target variable
Supervised Machine Learning algorithms outputs a hypothesis, which maps x to y.Kurtosis
/notes/kurtosis/
Sun, 04 Mar 2018 00:00:00 +0000/notes/kurtosis/Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. That is, data sets with high kurtosis tend to have heavy tails, or outliers. Data sets with low kurtosis tend to have light tails, or lack of outliers.
In effect, Kurtosis explains whether the samples concentrate too much at the centre or not.
A kurtosis value near 0 indicates that the data follow the normal distribution.Statistics Distribution with Python
/notes/stat-distribution/
Sun, 04 Mar 2018 00:00:00 +0000/notes/stat-distribution/Click to view Gist...Variability
/notes/variability/
Sun, 04 Mar 2018 00:00:00 +0000/notes/variability/Measures of variability describe the amount of variability or spread in the data. The most common measures of variability are the range, the interquartile range (IQR), variance, and standard deviation.
Range The range is a measure of the total spread of values in a quantitative dataset. Unlike other more popular measures of dispersion, the range actually measures total dispersion, more literally, as the difference between the largest and the smallest value in a dataset.Correlation
/notes/correlation/
Sat, 03 Mar 2018 00:00:00 +0000/notes/correlation/Correlation is
" the degree of association between two variables" " the measure of the strength of association among the different variables."
Correlation does NOT
" imply causation"
To emphasize that a correlation between two variables does not imply that one causes the other. For example; Sales of personal computers and athletic shoes have both risen strongly in the last several years and there is a high correlation between them, but you cannot assume that buying computers causes people to buy athletic shoes (or vice versa).Artificial Neural Network Learning
/notes/nn-backpropagation/
Thu, 01 Feb 2018 00:00:00 +0000/notes/nn-backpropagation/1. Overview Artificial neural networks (ANNs) are a powerful class of models used for nonlinear regression and classification tasks inspired by biological neural computation. Significance of this notes is to give the clarity and completeness on the Neural Network Learning process and mathematics behind it!
2. Neural Network Learning Neural Network consist of input, hidden, or output layers. There is only one input layer and one output layer but the number of hidden layers is unlimited.Artificial intelligence is the future
/blog/artificial-intelligence-is-the-future/
Mon, 08 Jan 2018 00:00:00 +0000/blog/artificial-intelligence-is-the-future/The market for Artificial Intelligence (AI) technologies is flourishing. Artificial intelligence is rapidly coming of age, survived the hype and poised to transform businesses and industries globally.
Gartner says AI technologies will be in almost every new software product by 2020. Billions of dollars are invested in new AI developments. IDC estimated that the AI market will grow from $8 billion in 2016 to more than $47 billion in 2020.Decision trees
/notes/decision-trees/
Fri, 23 Jun 2017 00:00:00 +0000/notes/decision-trees/1. Overview Decision Tree a supervised learning algorithms that can be used for classification or regression predictive modeling but mostly used in classification problems. Classically, this algorithm is referred to as decision trees. The representation for the CART model is a binary tree.
2. Intuition A binary tree is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child.P1: Titanic Disaster
/projects/comingsoon/
Thu, 22 Jun 2017 00:00:00 +0000/projects/comingsoon/1. Overview The objective of this project is to follow a step-by-step walk-through, explaining each step and rationale for every decision made while executing this project. This project aims to explore the different steps while applying the tools of machine learning to predict survivors and reasoning out why they survived.
Learn organically. What does this mean? Try less depending on the black box explanation/analysis. Try understanding the concept behind the analysis or the steps.