Permutations and Combinations

Permutations When the order does matter it is called Permutation. In other words, a Permutation is an ordered Combination. We should really call this a "Permutation Lock"! There are basically two types of permutation: Repetition is Allowed: such as the lock above. It could be "00000". No Repetition:...

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Mean vs Variance vs Standard Deviation

Mean: The mean is the average of the numbers. Variance: Variance is nothing but the average of the squares of the deviations. Standard Deviation: Standard Deviation is the square root of the numerical value obtained while calculating variance. Definition of Variance In statistics, variance is...

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Simple Linear regression

Let’s take a look at this dataset. It’s related to the Co2 emission of different cars. It includes Engine size, Cylinders, Fuel Consumption and Co2 emissions for various car models. The question is: Given this dataset, can we predict the Co2 emission of a car, using another field, such as Engine...

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Regression Models

The regression model is a powerful method that allows you to examine the relationship between two or more variables of interest. In other word, Regression models (both linear and non-linear) are used for predicting a real value, like salary for example. If your independent variable is time, then you...

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Understanding Deep Learning with TensorFlow playground

The TensorFlow playground can be used to illustrate that deep learning uses multiple layers of abstraction. First, notice blue represents +1, orange represents -1, and white represents 0. Let’s start with the default classification example. There are 4 datasets. The four datasets: circular,...

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What is TensorFlow? Introduction, Architecture

What is TensorFlow? Currently, the most famous deep learning library in the world is Google's TensorFlow. Google product uses machine learning in all of its products to improve the search engine, translation, image captioning or recommendations. To give a concrete example, Google users can experience a faster and more refined the search with AI. If the user types a keyword in the search bar, Google...

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Activation functions and what are it uses in a Neural Network Model

Activation functions are really important for an Artificial Neural Network to learn and make sense of something really complicated and Non-linear complex functional mappings between the inputs and response variable. They introduce non-linear properties to our Network. Their main purpose is to convert...

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Introduction of the perception/neuron

Before we jump straight into neural networks we need to understand the individual components first such as a single neuron. Artificial neural networks (ANN) actually have a basis in biology so we're going to see how we can attempt to mimic biological neurons of an artificial neuron (otherwise known...

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Machine Learning

What is machine learning? Machine learning algorithms are algorithms that learn (often predictive) models from data. I.e., instead of formulating “rules” manually, a machine learning algorithm will learn the model for you. in another word, Machine learning is a technique to achieve AI through algorithms trained with data. There are three ways in which machines learn: Supervised Learning: Supervised...

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Deep Learning

Deep learning is a subset of machine learning which in turn is a subset of artificial intelligence. Artificial intelligence is a technique that enables a machine to mimic human behaviour. Machine learning is a technique to achieve AI through algorithms trained with data and finally, deep learning is...

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Machine Learning Algorithms

Deep Learning Deep learning is a subset of machine learning which in turn is a subset of artificial intelligence. Artificial intelligence is a technique that enables a machine to mimic human behaviour. Machine learning is a technique to achieve AI through algorithms trained with data and finally,...

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