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Check If The String Is A Palindrome
You are given a string ‘S’. Your task is to check whether the string is palindrome or not. For checking palindrome, consider alphabets and numbers only and ignore the symbols and whitespaces. Note : Example : Input format : Output format : Note : Follow Up : Constraints : Implementation in Python Read more
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Implementing Ridge Regression from Scratch
For Linear Regression in Machine learning with two variables we have to find 2 coefficient. In case of overfitting these 2 coefficients can be very high. Y=mX+c So to handle this, Idea is that we want to reduce the value of coefficient(m). By doing this biasness can increase but variance decreases. Which is called bias… Read more
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Titanic – Advanced Feature Engineering Tutorial
Introduction I decided to write this kernel because Titanic: Machine Learning from Disaster is one of my favorite competitions on Kaggle. This is a beginner level kernel which focuses on Exploratory Data Analysis and Feature Engineering. A lot of people start Kaggle with this competition and they get lost in extremely long tutorial kernels. This is a short kernel compared… Read more
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Feature Engineering in Machine Learning
Introduction Feature engineering, often hailed as the cornerstone of machine learning, holds the power to transform raw data into actionable insights. In the realm of predictive modeling, where the quality of features can significantly influence model performance, mastering the art of feature engineering is indispensable. In this comprehensive guide, we’ll embark on a Titanic journey… Read more
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Avoiding Overfitting Through Regularization
With thousands of parameters you can fit the whole zoo. Deep neural networks typically have tens of thousands of parameters, sometimes even millions. With so many parameters, the network has an incredible amount of freedom and can fit a huge variety of complex datasets. But this great flexibility also means that it is prone to… Read more
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Regression and Classification Multi Layer Perceptrons
Introduction In the dynamic landscape of machine learning, Multilayer Perceptrons (MLPs) emerge as formidable tools capable of handling both regression and classification tasks with finesse. Whether you’re predicting housing prices or sorting emails, understanding how to tailor MLP architectures and activations is pivotal for optimizing performance. Regression MLPs Crafting an MLP architecture for regression tasks… Read more