In this video, you will discover one of the popular types of Machine Learning i.e. Classification which again falls under supervised learning. Linear regression and its types we have already seen check the links below, now let’s focus on the very first algorithm…

In this video, we will see one of the most popular examples of classification in Machine Learning i.e. Iris Dataset. Video helps you understand how to use Logistic Regression algorithm in Machine learning using Jupyter Notebook.

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In this video, we are going to understand Feature engineering, which will help us get better accuracy and improve our Machine Learning model using Correlation Coefficient Matrix

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In this video, we are going to understand Heart Disease Prediction Using Logistic Regression which shows examples of Classification Algorithm in Machine Learning. We also discussed how to improve accuracy and split data into training and testing.

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In this video, we are going to understand Math Behind Logistic Regression which shows how does really logistic regression algorithm works and the logic behind it. We will also understand how a machine draws a line to classify data using the Sigmoid function.…

In this video, we are going to understand Confusion Matrix which helps you to measure the accuracy better. Although accuracy is not a good measure, precision, recall, and f1 score are what we will study in the next video but to calculate precision, recall…

In this video, we are going to understand Precision, Recall, and F1 scores which helps you to measure the accuracy better. Measuring only accuracy is not sufficient for all data set, this is where precision, recall, and f1 score come into the picture.

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In this video, we are going to understand Naive Bayes Classification with Tennis dataset example which helps you understand how does Naive Bayes algorithm calculates answer using probability theory.

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In this video, we are going to understand Types of Naive Bayes and the Pros and Cons of Naive Bays, Eventually which will help us understand the Applications of this classifier and where to use and where not to use

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In this video, We are going to Understand how to work with Machine Learning Classification Technique using a Naive Bayes Classifier. We Considered most Popular Classification Iris Dataset using Scikit Learn Library

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In earlier videos, we have seen What is Naive Bayes and Demo on Gaussian Naive Bayes with Iris DataSet. This video will help you understand How and When to use Ga, Multinomial, and Bernoulli's Naive Bayes Algorithm.

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This Video Helps You to Understand the Decision Tree Algorithm from the Basics and How Does Attribute Split is Decided Using Entropy?

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