Model Training basically involves learning an equation that minimizes the loss between the actual and predicted value. By learning an equation, means to adjust the various parameters/weights in the equation. Here’s where optimization comes in play. An optimizer is a method or algorithm to update the various parameters that can…

Code conventions, and libraries to use while writing codes in Python which will make your code consistent, efficient, and easy to debug/read. — A better programmer is not the one who can write codes that a computer can understand but it’s the one, whose code is easily understood by its colleagues, and further modifications can be added without much affecting the previous code. In this article, I am listing down some of the…

Improve code readability with these simple tools. — We often forget to follow basic Code Conventions when writing Python code, since we know it’s not very restricted and will still run the code. However, it decreases the Code Readability and can also cause unexpected behavior in its logic, which becomes hard to trace as the project grows. Here…

What’s a Loss Function? It’s how we can find out that our Algorithm is performing well or not, the main aim of algorithm is to reduce this loss so as to get our predictions close to Actual values. Before choosing a Loss function that will be appropriate for your model…