Check out the original notebook here. The goal of this blog is to demonstrate how data augmentation can enhance the development of a model pipeline capable of predicting the sentiment behind cust...

Hey everyone! I want to share an amazing discovery I made recently about Jupyter Notebook. Let me give you a bit of context so you can appreciate how I stumbled upon this gem. As a data scientist, ...

Check out the original notebook here. Why is initialization essential to deep networks? It turns out that if you do it wrong, it can lead to exploding or vanishing weights and gradients. That mea...

Check out the original notebook here. Normaly there are two ways to train a model. Using a “closed form” equation, i.e., a equation composed by a finite number of constants, variables and operati...

What is Constraint Satisfaction Problem? A Constraint Satisfaction Problem (CSP) consists of: a set of variables $\mathcal{X} = \{x_1,…,x_n\}$, a set containing the domains of each variable ...

This post aims to unveil the remedy for a recurring issue I’ve encountered each time I’ve had to set up a fresh Linux OS from scratch. I find great ease in conducting my entire workflow within the ...

Check out the original notebook here. Table of content Definitions Template for programs Built in types The typedef keyword Code examples Definitions Before digging into code examp...

Check out the original notebook here. In this tutorial we will take a closer look at (popular) activation functions and their effect on optimization properties in neural networks. Picking a good...

Check out the original notebook here. Categorical data requires special care. Data like language characters ‘a’, ‘b’, ‘c’ etc. are usually represented as integers 0, 1, 2, etc. Do not use integer...

Check out the original notebook here. Hidden code from sklearn.datasets import fetch_openml from sklearn.model_selection import StratifiedKFold from sklearn.dummy import DummyClassifier fr...