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Pythontpoints.com is now changes to pythontpoint.org, please join us and build your career with us... learn free tech courses like java, python, ai, power bi and many more...
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Learn about Steps for PCA algorithm : 1. Getting the dataset :
Firstly, we need to take the input dataset and divide it into two subparts X and Y, where X is the training set, and Y is the validation set.
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Learn about Principal Component Analysis : Principal Component Analysis is an unsupervised learning algorithm that is used for the dimensionality reduction in machine learning.
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Learn about Categories of Hyperparameters : Broadly hyperparameters can be divided into two categories, which are given below:
1. Hyperparameter for Optimization
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Learn about Hyperparameters in Machine Learning : Hyperparameters in Machine learning are those parameters that are explicitly defined by the user to control the learning process.
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Learn about Techniques of Regularization : There are mainly two types of regularization techniques, which are given below:
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Learn about Regularization in Machine Learning : Regularization is one of the most important concepts of machine learning. It is a technique to prevent the model from overfitting by adding extra information to it.
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Learn about Unsupervised Machine Learning Introduction : The purpose of Machine Learning model is to understand the given data and then make prediction without human intervention.
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Learn about Naïve Bayes Classifier Algorithm : Naïve Bayes algorithm is a supervised learning algorithm, which is based on Bayes theorem and used for solving classification problems.
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Learn about What is Decision Tree ? : Decision Tree is a supervised machine learning algorithm mostly preferable for Classification problem but it can be used for both Classification as well as Regression problem.
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Learn about Confusion Matrix & Cost Matrix : Confusion & Cost Matrix helps in calculating the accuracy, cost and various other measurable factors in classification problem.
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Learn about Iris flower classification using KNN : The Iris flower data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems.
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Learn about KNN(K-Nearest-Neighbour) : K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique.
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Learn about Support Vector Machine(SVM) in Machine Learning Tutorial : SVM is a supervised machine learning algorithm which can be used for regression and classification.
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Learn about Sigmoid Function in machine learning : The sigmoid function, also called logistic function gives an ‘S’ shaped curve that can take any real-valued number and map it into a value between 0 and 1.
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Learn about Sigmoid Function in machine learning : The sigmoid function, also called logistic function gives an ‘S’ shaped curve that can take any real-valued number and map it into a value between 0 and 1.
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Learn about What is Logistic Regression in machine learning : Logistic regression is a statistical and machine learning model used for binary classification tasks.
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Learn about Simple Linear Regression in machine learning Using Python : Simple Linear Regression is a Supervised machine learning Algorithm coming under the concept of regression.
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Silan Software wishing you all a Happy Kartika Purnima... Kartika Purnima is a Hindu and Jain cultural festival that is celebrated on Purnima...

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Learn about Supervised Machine Learning : Supervised learning is one type of Machine Learning where we have input variables (x) and an output variable (Y) and we use an algorithm to find the value of y by taking the value of X. Here y value may be a continuous value or categorical value.
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Learn about Types of Machine Learning : There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning.
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Learn about Framework for Developing Machine Learning Models : Developing a machine learning model can be a complex process that requires careful planning and attention to detail.
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Learn about Why Machine Learning : Machine learning has become increasingly popular because of its ability to automate tasks that were previously done manually, and to find patterns and insights in large datasets that would be difficult for humans to identify on their own.
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Learn about Machine Learning Introduction : Machine learning is a type of artificial intelligence that involves training computer algorithms to make predictions or decisions based on patterns in data.
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Learn about Introduction to analytics and machine learning : Analytics and machine learning are two important fields that are used to extract insights and make predictions from data.
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Learn about What is Artificial Intelligence? : (AI) refers to the ability of machines to perform tasks that would normally require human intelligence to accomplish.
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Learn about What is Neural Network : Neurons (also called neurons or nerve cells) are the fundamental units of the brain and nervous system, the cells responsible for receiving sensory input from the external world, for sending motor commands to our muscles, and for transforming and relaying the electrical signals at every step in between.
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