I am a Graduate from Bangladesh. area of interest are Machine Learning, Deep Learning,RNN and Computer vision
Nothing here yet.
Nov 28, 2023 · 3 min read · 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 model is trained with features from the data that are not necessarily co-related with the target vector...
Join discussion
May 7, 2023 · 2 min read · In short,PCA(Principal Component Analysis) is a dimensional reduction technique used for high dimensional dataset(i.e many columns) , it's basically taking a snap shot of the dimension of data from an angle so that we can capture the max varience of ...
Join discussionApr 9, 2023 · 1 min read · - 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 the derivation of sigmoid function is ranging between 0 to 0.25. so in a multi hidden layer neural n...
Join discussionFeb 2, 2023 · 2 min read · Pros: The theorem is very crucial for computationally intensive problems, handling missing data or irrelevant features Cons: As the algorithm assumes that the feature or relation between variables are independent it sometimes cause inaccuracy as in r...
Join discussionJan 30, 2023 · 1 min read · 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 . In short it's a line(for (2D)) or hyperplane(n_dimension) that separates the plot(or points in the pl...
Join discussion