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Logistic Regression

Logistic regression is a well-known algorithm used in the field of statistics and machine learning. It is best used to predict responses which are categorical in nature (yes or no). Similar to linear regression, the goal of this algorithm is to find the values for the coefficient that weight each input variable. Unlike linear regression…
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Bias Variance and Tradeoff

Meaning of Bias and Variance? Bias: how unfair is something towards other Variance: how likely something changes with respect to others Thing to remember? High Bias: under fitting High Variance: over fitting What is High Bias and High Variance? Assume there are two examiners determining weather forecast. Where it rains only when it is humid…
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The Bias and Variance tradeoff

Developing the machine learning models isn’t so hard nowadays, due a lot of frameworks and libraries that give build-in functions to easily implement some fancy model. However, it’s important to understand the theory behind all practical implementation in order to build more accurate models. So in this topic will be discussed the theoretical understanding of…
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Piecewise Linear Regression

Real world data is not always linear. Many cases it is very difficult to fit a line and get an perfect model on non linear and non monotonic datasets. While one can resort to complex models like SVM, Trees or even Neural Network, it comes with cost of interpret-ability and explain-ability Is there a middle…
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The Awesomeness of Viterbi

Automatic Speech Recognition (ASR) refers to the task of automatically convert a speech signal into text. Nowadays, we all use this marvelous technology without even wonder about its complexity. Currents state of the art system are based on different Deep Neural Networks Architectures (the most basic one is the hybrid Deep Neural Network- Hidden Markov Model (DNN-HMM))…
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Provide an example of an application/business use case of Natural Language Processing (NLP)

Current approaches to natural language processing (NLP) combine both linguistic or grammatical approaches while machine learning (ML) techniques are used. On the other hand, Digital marketing and being more effective in this business is one of the main efforts of A.I and ML applications which will give more and more percentage of convergence. I believe…
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Sentiment Analysis using NLP

Sentiment analysis using Natural Language Processing “This is almost correct.” Can you tell whether it is in a positive or negative sense? We all might have been in such a conundrum in our lives. This is called as sentiment analysis in technical terms. Sentiment analysis has been a crucial part of understanding the view, perspective…
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There’s a lot more to a text!

Sentiment analysis is one of the significant applications of Natural Language Processing. There’s a lot more to human communication than just the objective definitions of their words. Understanding this sentiment aspect of a text; is really useful to assess the public reviews or any other broad public opinion that surfaces the social media. The ability…
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Pre-emptive Identification of online grooming using NLP Chatbots

Using Chatbots to identify is not new [1-6], but more work is required given its estimated 1 out of 7 children online will receive a sexual solicitation [7] and the heinous nature of the crime. An multi-layered approach proposed below. Chatbots: We specifically recommend because they are more interactive, have benefited from recent algorithm improvements,…
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NLP for the diagnosis of the mental health illness

Mental health problems like depression and anxiety are difficult to identify in their early stages. According to Stanford Natural Language Processing Research Group,  in the U.S. alone, 43.6 million adults (18.1%)experience mental illness each year. The longer the individual is without treatment, worse is the impact on the health of the individual. NLP for the diagnosis…
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