This article covers five parts:

1. What is MobileNet?
2. The Architecture of MobileNet.
3. Depthwise Separable Convolution.
4. Difference between Standard Convolution and Depthwise separable convolution.
5. MobileNet with Python (With code).

What is MobileNet?

As the name applied, the MobileNet model is designed to be used in mobile applications, and it is TensorFlow’s first mobile computer…

This article covers five parts:

1. What is a Naïve Bayes algorithm?
2. Naïve Bayes algorithm application
3. Pros of Naïve Bayes
4. Cons of Naïve Bayes
5. Naïve Bayes with python(With code)

What is the NaïveBayes Algorithm?

Naïve Bayes Algorithm is one of the popular classification machine learning algorithms and is included in supervised learning. that helps to classify…

This article covers six parts:

1. What is K-Nearest Neighbor (K-NN)?
2. To find “K” in k Nearest Neighbor?
3. distance functions
4. Pros K-Nearest Neighbor
5. Cons of K-Nearest Neighbor
6. K-Nearest Neighbor with Python(With code)

In this article, we will explore and also see the code of the famous supervised machine learning algorithm, “K-Nearest…

This article covers eight parts:

1. What is the support vector machine?
2. About Hyperplane.
3. How does it work in linear separable
4. How does it work in linear non-separable
5. Advantages of Support Vector Machine (SVM)
6. Disadvantages of Support Vector Machine (SVM)
7. Applications of Support Vector Machine (SVM)
8. Support Vector Machine with Python…

This article covers four parts:

1. What is a Random Forest?
2. Random Forest algorithm Application.
3. Advantages of Random Forest
4. Random Forest with Python (with code)

In this article, we will explore and also see the code of the famous supervised machine learning algorithm, “Random Forests.”

What is a Random Forest?

Random forests are bagged decision tree…