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Machine learning

Maths 101 : Part 7: Estimating Confidence Intervals

In statistics, a confidence interval (CI) is a type of interval estimate which we compute using the statistics of the observed data. The interval has an associated confidence level that, loosely speaking, quantifies the level of confidence that the value Read more…

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By admin, 6 yearsMarch 23, 2019 ago
Machine learning

Maths 101 : Part 6: Measuring relationship between two Random Variables

Suppose you have taken the data for heights and weights of students in class and you want to figure out the correlation between heights and weights of students. The relation between these two parameters is defined mathematically by one of Read more…

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By admin, 6 yearsMarch 11, 2019 ago
Machine learning

Maths 101: Part 5: Different Types of Distribution

Types of Distributions Bernoulli and Binomial distribution A Bernoulli random variable has two possible outcomes: 0 or 1. A binomial distribution is the sum of independent and identically distributed Bernoulli random variables. So, for example, say I have a coin, Read more…

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By admin, 6 yearsFebruary 23, 2019 ago
Machine learning

Maths 101: Part 4: PDF, Central Limit Theorem and Chebyshev’s inequality

Populations and Samples The main difference between a population and a sample has to do with how observations are assigned to the data set Population Includes all of the elements from a set of data. Sample Consists of one or Read more…

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By admin, 6 yearsFebruary 9, 2019 ago
Machine learning

Maths 101: Part 3: Random variables and Normal Distribution

Random Variables The term random variable is not very descriptive. A better term is measurement function.Consider tossing a fair six-sided die. There are only six outcomes possible, Ω = {1, 2, 3, 4, 5, 6} As we know, if the Read more…

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By admin, 6 yearsJanuary 26, 2019 ago
Career Advice

Why every software engineer/ml engineer/data scientist should write a blog

As software developers, we try to tend to work with a lot of different technologies. We also face and solve a lot of technical challenges as part of our daily work. So what could be some of the reasons for Read more…

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By admin, 6 yearsJanuary 19, 2019 ago
Golang

Golang vs python: Arguments in favor of python

Dynamic typing Majority of people have a single problem with a python feature and drumrolls it’s Ducktyping. In short “If it walks like a duck and it quacks like a duck, then it must be a duck”. I agree that Read more…

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By admin, 6 yearsJanuary 8, 2019 ago
Machine learning

Applying Exploratory Data Analysis on IRIS dataset

Iris dataset is one of the most easiest and straightforward datasets to use. In Iris dataset, we can represent dataset as a matrix in the following format. Petal length Petal Width Sepal length Sepal width Flower-1 Flower-2 : Flower-n However, Read more…

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By admin, 6 yearsDecember 15, 2018 ago
Machine learning

Math 101: Part 2: Measures of central tendency and Skewness

Measures of central tendency To represent a quick summary of data we use several mathematical methods. These methods usually try to determine where the center of the dataset lie. There are three mathematical measures and they all have their own unique Read more…

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By admin, 7 yearsDecember 4, 2018 ago
Machine learning

Maths 101: Part 1: Data Types and their visualization

Using the right Graphs are very important for representing the right type of data.We can say Data in statistics is of the following types   For reading the details on all the different data types read here. https://towardsdatascience.com/data-types-in-statistics-347e152e8bee   For Read more…

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By admin, 7 yearsDecember 4, 2018 ago

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