The Tug of War: Accuracy and Interpretability in Machine Learning Models
Model prediction accuracy is crucial, but not always the top priority. Sometimes, we may need to sacrifice some accuracy to make the model m
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shivamshinde92722
Feb 95 min read
Unlocking the Potential of Pandas: Must-Know Methods for Efficient Data Handling in Python
In this article, you will learn the very important and must-know methods present in the Python Pandas library.
shivamshinde92722
Jan 237 min read
Guardrails for ML and DL Models: A Deep Dive into Regularization Techniques
This article will explain the concept of regularization in ML and DL. The article will also introduce readers to some of the most famous reg
shivamshinde92722
Aug 27, 20234 min read
From Raw to Refined: A Journey Through Data Preprocessing — Part 3: Duplicate Data
This article will explain how to identify duplicate records in the data and, the different ways to deal with the problem of having duplicate
shivamshinde92722
Aug 5, 20236 min read
From Raw to Refined: A Journey Through Data Preprocessing - Part 2: Missing Values
This article will explain the concept of missing values in the data and the ways to deal with data containing missing values.
shivamshinde92722
Jul 29, 20233 min read
From Raw to Refined: A Journey Through Data Preprocessing — Part 1: Feature Scaling
This article is the part 1 of the Data Preprocessing series. In this part, I explain the feature scaling step of the preprocessing.
shivamshinde92722
Jul 22, 20234 min read
Be Confident in your Machine Learning Models with the help of Cross-Validation
Cross-validation is a go-to tool to check if your machine-learning model is reliable enough to work on new data. This article will discuss c
shivamshinde92722
Jul 2, 20234 min read
From Many to Few: Tackling High-Dimensional Data with Dimensionality Reduction in Machine Learning
This article will discuss the curse of dimensionality in machine learning problems and dimensionality reduction as a solution for the...
shivamshinde92722
Apr 14, 20234 min read
Striking the Right Balance: Understanding Underfitting and Overfitting in Machine Learning Models
This article will explain the basic concept of overfitting and underfitting from the machine learning and deep learning perspective.
shivamshinde92722
Dec 23, 20223 min read
A Simple Approach to Creating Custom Transformers Using Scikit-Learn Classes
In this article, I will be explaining how to create a transformer according to our processing needs using Scikit-Learn classes
shivamshinde92722
Dec 15, 20225 min read
Using Scikit-Learn Pipelines to Automate the Machine Learning Model Training and Predictions
In this article, I will try to explain the theory and the use of Scikit-Learn’s pipelines class using a coding example of...
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