Category: Machine Learning

Diabetes Prediction Using Machine Learning

In this article, we will be predicting that whether the patient has diabetes or not on the basis of the features we…

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Forest Fire prediction using Machine Learning – Analytics Vidhya

Forest, bush, or vegetarian fire, can be described as any uncontrolled and non-prescribed combustion or burning of plants in a natural setting such as a forest, grassland, etc. In this article we are not determining if a forest fire will take place or not, we are predicting the confidence of the forest fire based on some attributes.
Well, the first question arises as that why we even need Machine learning to predict forest fire in that particular area? So, yes the question is valid that despite having the experienced forest department who have been dealing with these issues for a long time why is there a need for ML, having said that answer is quite simple that the experienced forest department can check on 3-4 parameters from their human mind but ML on other hand can handle the numerous parameters whether it can be latitude, longitude, satellite, version, and whatnot, so dealing with this multi-relationship of a parameter that is responsible for the fire in the forest we do need ML for sure!

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Random Forest Algorithm for Absolute Beginners in Data Science

Random forests are a supervised Machine learning algorithm that is widely used in regression and classification problems and produces, even without hyperparameter tuning a great result most of the time. It is perhaps the most used algorithm because of its simplicity. It builds a number of decision trees on different samples and then takes the majority vote if it’s a classification problem.

I am assuming you have already read about Decision Trees, if not then no need to worry we’ll read everything from start. In this article, we’ll figure out how the Random Forest algorithm works, how to use it, and the math intuition behind this simple algorithm.

Before learning this algorithm let’s first see what are Ensemble techniques.

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How Machine Learning can be used with Blockchain Technology?

Blockchain technology has been trending in recent years. This technology allows a secure way for individuals to deal directly with…

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Top Machine Learning-Based Emotion Recognition Tools

UCLA is embarking on a three-year study to better understand the impact of “sleep, physical exercise, heart rate, and daily…

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AutoML: An Introduction Using Auto-Sklearn and Auto-PyTorch

AutoML is a broad category of techniques and tools for applying automated search to your automated search and learning to…

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Facebook Loves Self-Supervised Learning. Period.

Facebook’s chief AI scientist Yann LeCun’s influence seems to have rubbed off on the team, taking a path less travelled – a journey towards…

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Loan Status Prediction using Support Vector Machine (SVM) Algorithm

You see, any bank, approves a loan based on the two most vital points: 1) How risky is the borrower…

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The Machine & Deep Learning Compendium

An open knowledge-sharing project . Hi! Nearly a year ago I announced the Machine & Deep Learning Compendium, a Google…

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A Bird’s Eye View of Research on Attention

The scientific study of attention began in psychology, where careful behavioral experimentation can give rise to precise demonstrations of the…

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An Introduction to Reinforcement Learning with OpenAI Gym, RLlib, and Google Colab

Get an Introduction to Reinforcement Learning by attempting to balance a virtual CartPole with OpenAI Gym, RLlib, and Google Colab….

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Industry vs Academia in Machine Learning

What things to consider while deciding Choosing careers in itself is difficult. Add the time commitment of 5–6 years for…

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Top 18 Low-Code and No-Code Machine Learning Platforms

Machine learning becomes more accessible to companies and individuals when there is less coding involved. Especially if you are just…

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Decision Tree Algorithm – A Complete Guide

What is a Decision Tree? It is a tool that has applications spanning several different areas. Decision trees can be…

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The Machine Learning Journey Of Aishwarya Srinivasan

Analytics India Magazine got in touch with Aishwarya Srinivasan, AI/ML Innovation Leader, Business Development, IBM, to understand her machine learning journey….

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A Gentle Introduction To Sigmoid Function

Whether you implement a neural network yourself or you use a built in library for neural network learning, it is…

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Email Spam Detection – A Comparative Analysis of 4 Machine Learning Models

This article aims to compare four different deep learning and machine learning algorithms to build a spam detector and evaluate…

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Automating Machine Learning Modelling

Creating a Machine Learning model is not a difficult task because Python provides ample libraries which can help in creating…

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MACHINE LEARNING STRATEGIES: WHY BUSINESSES ARE FAILING AT IT?

Data continues to remain a significant obstacle in various phases of preparation and embracing an AI procedure. In the Rackspace…

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