Beyond Labels: The Magic of Autoencoders in Unsupervised Learning
In a world where labeled data is often scarce, autoencoders provide a powerful solution for extracting insights from unstructured data
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shivamshinde92722
Oct 92 min read
Efficient Backpropagation: Exploring the Role of Jacobian Matrices and the Chain Rule
In this article, I will tough upon the topic of Jacobian matrix and how it is used in the back-propagation operation of deep learning.
shivamshinde92722
Sep 122 min read
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
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
Jun 29, 20233 min read
Unlocking the Potential of Text: A Closer Look at Pre-Embedding Text Cleaning Methods
This article will discuss different cleaning techniques that are essential to obtain maximum performance from textual data
shivamshinde92722
Jan 14, 20234 min read
Deep Dive into Gated Recurrent Units (GRU): Understanding the Math behind RNNs
Gated Recurrent Unit (GRU) is a simplified version of Long Short-Term Memory (LSTM). Let’s see how it works in this article.
shivamshinde92722
Jan 6, 20233 min read
From Vanilla RNNs to LSTMs: A Practical Guide to Long Short-Term Memory
Long short-term memory (LSTM) networks have become a go-to tool for tasks like machine translation, language modeling, and speech recognitio
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