How to evaluate your image classification model – Here is one of the trained model for MNIST image classification. As a response to the common… Read More »How to evaluate your image classification model
Support vector machine is one of the best nonlinear supervise to machine learning models. Given a set of labeld training data SVM will help us… Read More »Support Vector Machines: All you need to know!
How to evaluate classification model – Confusion Matrix, The earliest reference to the concept had been made by British Statistician Karl Pearson in 1904, which… Read More »How to evaluate classification model: Confusion Matrix
Softmax, Cross Entropy – Hello everyone! Welcome to part two of the image classification with Pytorch series. In this article, we are going to continue… Read More »Softmax, Cross Entropy: Image Classification with Pytorch
Backpropagation and Gradient Descent – In this article, we are going to continue our project by explaining two important concepts in deep learning: backpropagation and… Read More »Backpropagation and Gradient Descent: Image Classification with Pytorch
K means clustering: Explained with Jupyter Notebook – In this tutorial, we are going to introduce K-means clustering algorithm. All right, let’s get started. K-means… Read More »K means clustering: Explained with Jupyter Notebook
Decision Tree: Important Things to Know – Decision Tree organized a series roots in a Tree Structure. It is one of the most practical methods… Read More »Decision Tree: Important Things to Know
Willump: Optimizing Feature Computation in ML Inference – Today, I’d like to talk to you about Willump, a statistically aware end-to-end optimizer for machine learning… Read More »Willump: Optimizing Feature Computation in ML Inference