K Nearest neighbour (KNN) is one of the most basic classification algorithms. It follows the assumption that similar things exist in close proximity to each other. The K-nearest neighbour algorithm calculates the distance between the various points whose category is known and then selects the shortest distance for the new data point. It is an … Read more
Naive Bayes is a classification algorithm which checks the probability of a test point belonging to a class. Unlike other algorithms, Naive Bayes is purely a classification algorithm. As explained in the last release this is the formula for the Bayes theorem and as the algorithm name suggests Naive Bayes is inspired by the Bayes … Read more
Probability vs. Statistics Probability is used to predict the likelihood of a future event. vs Statistics are used to analyze past events Basics of Probability Probability, in simple terms, is the likelihood of a situation happening. When unsure of the outcome, the probability can be calculated to know its chances. Probability(Event)=(Number of favourable outcomes of … Read more
What is an activation function? Activation functions get their names from being used in neural networks as they decide whether a particular neuron should be activated. In the context of this release, the sigmoid function will be discussed in detail as it is used in the logistic regression algorithm for binary classification. Sigmoid Activation function … Read more
The Advantages of SAN Architecture Image Source: Link Sharing storage typically simplifies storage administration and adds flexibility because cables and stockpiling devices are not physically relocated to move storage from one server to the next. Other advantages include the ability to boot servers directly from the SAN. Because the SAN can be rearranged so that … Read more
A storage area network (SAN) is a high-speed channel or subnetwork that links and provides shared pools of storage systems to different servers. Memory availability, as well as accessibility, are significant considerations in enterprise computing. Conventional direct-attached disc deployments within separate servers could be a simple and low-cost option for several enterprise systems. Still, the … Read more
Lets us try to implement logistic regression from scratch in python. Recommended to be read after the Neural Networks release. Importing necessary libraries import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) import matplotlib as plt The dataset we will be using is Pima-Indians-diabetes-database … Read more
Logistic regression is one of the most popular algorithms for classification problems. It is called regression even though it is not a regression algorithm because the underlying technology is similar to Linear Regression. The term “logistic” comes from the statistical model used (logit model). As seen in earlier releases, classification algorithms are used to classify … Read more
In machine learning, classification is the method of classifying data using certain input variables. A dataset with labels given (training dataset) is used to train the model in a way that the model can provide labels for datasets that are not yet labeled. Under classification, there are 2 types of classifiers: Binary Classification Multi-Class Classification … Read more
In machine learning, classification is classifying data using certain input variables. A dataset with labels given (training dataset) is used to train the model in a way that the model can provide labels for datasets that are not yet labeled. Under classification, there are 2 types of classifiers: Binary Classification Multi-Class Classification Here let’s discuss … Read more
