Cross Validation In Machine Learning | Cross Validation | Machine Learning Tutorial | Intellipaat

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#CrossValidationInMachineLearning #CrossValidation #WhatisCrossValidation #MachineLearningTutorial #MachineLearning #Intellipaat

In this video on "Cross-Validation in Machine Learning," we will look into the crucial concept of What is Cross-Validation. Then we will go through the different types of cross-validation methods. Lastly, we will show you the implementation of Cross-Validation

🔵 Following topics are covered in this session:
00:00 - Introduction
00:55 - Why Cross-Validation
02:19 - What is Cross-Validation
04:43 - Different Types of Cross-Validation Methods
10:57 - Benefits of Cross-Validation
12:07 - Demo Implementation of Cross-Validation

✅ What is cross-validation and why is it used?
Cross-validation is a very useful technique to assess the effectiveness of a machine learning model, particularly in cases where you need to mitigate overfitting. It is also of use in determining the hyperparameters of your model, in the sense that which parameters will result in the lowest test error.

✅ What is cross-validation for dummies?
Some of the data is removed before training begins. Then when training is done, the data that was removed can be used to test the performance of the learned model on ``new'' data. This is the basic idea for a whole class of model evaluation methods called cross-validation.

✅ What is the main point of cross-validation?
Cross-validation helps us to avoid overfitting of the model and it also helps to increase the generalization accuracy which is the accuracy of the model on unseen future points.

➡️ About the Course
Explore this Machine Learning course taught by IIT Madras faculty and industry experts that will help you master Machine Learning algorithms. This ML certification training will help you master Python, machine learning algorithms, statistics, and AI skills. Enroll in this training course and get your Machine Learning certification from IITM Pravartak.

➡️Who should take this course?
Experts have designed our ML course so that anyone, from a fresher/undergraduate or undergrad to a professional seeking a career change, can benefit from it.

✅ Key Features - (Course Features)
👉🏼50+ Live sessions across seven months
👉🏼218 Hrs Self-paced Videos
👉🏼200 Hrs Project & Exercises
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✅Preparatory Session - Linux and Python
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Комментарии

Nicely explained with the help of examples.. 👏

rsrqugf

Cross validation basically works on how the test data perform its accuracy to avoid over fitting it has 4 types to achieve this validation on test data

Ranganadhamkrishnachaitanya

What is the difference between k-fold cross-validation and stratified k-fold cross-validation?

rsrqugf

What is the risk of overfitting in cross-validation?

kabeer-oljo

Why is random shuffling important in cross-validation?

phqnbpt

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