#machine-learning
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Hello ML enthusiast! My todays post is about "Overfitting" or high Variance of a model (both ML or DL) .So, Let's right jump into it. Sometimes ML...
Key points: Covariance, Linear Transformation,Eigenvectors, Eigenvalues ยท In short,PCA(Principal Component Analysis) is a dimensional reduction technique...
- in a back propagation,we use Relu (Rectified linear unit) activation function more then Sigmoid function but why? -before I explain,i hope you know...
Pros: The theorem is very crucial for computationally intensive problems, handling missing data or irrelevant features Cons: As the algorithm assumes...
It took me a while to totally understand the concept of Support vector Machine, which is mainly used for supervised data to classify or regression ....
