Hi everybody, In the last post, I depicted how to implement linear regression based on inverse matrix approach or normal equation using both Scikit-learn and TensorFlow libs. Though the approach gives us a concise answer, it cost the computational memory. The larger dataset is, the more computation need to be calculated. Thus, today, I would … Continue reading LINEAR REGRESSION (2) – NEURAL NETWORK APPROACH

# Category: Supervised Learning

# LINEAR REGRESSION (1) – MATRIX INVERSE APPROACH

Hi everybody, Today, I would like to talk about the linear model for regression task in this post. While you have seperate labels (which may be (0 and 1) or (-1 and 1)) in classification tasks, the outputs in regression are continuous (i.e. they are arbitrary numbers lie in particular ranges). On the other hand, … Continue reading LINEAR REGRESSION (1) – MATRIX INVERSE APPROACH