Machine Learning Diaries

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Everything you need to know about identifying hallucinations by LLMs
“Why is this misleading?”: Detecting News Headline Hallucinations with Explanations
 • 
Priyanka Nath
DiffGrad : Is it the right optimization method for training your CNNs?
Learn about DiffGrad - optimizer that solves the overshooting problem of Adam
 • 
Priyanka Nath
How to apply Boosting when the Data Labels are Noisy and Uncertain ?
LocalBoost - Local Boosting for Weakly-Supervised Learning
 • 
Priyanka Nath
What is Ant Colony Optimization and how does it help?
Deep dive into mechanics and applications of Ant Colony Optimization
 • 
Sheryl Bellary
A Look Into The Emerging Domain of Metric Learning
All about metric Learning and the impact it makes on the world of computer vision
 • 
Joshua Raj
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Everything you need to know about Activation Functions
 • Joshua Raj
1
Layman's Guide to Lottery Ticket Hypothesis In Neural Network
 • Joshua Raj
2
Here is what you need to know about Sparse Categorical Cross Entropy in nutshell
 • Sarthak Kedia and Priyanka Nath
Everything you need to know about Distributed training and its often untold nuances
 • Joshua Raj
OptFormer: Google's Improved Hyperparameter Optimization Technique
Optimizers with Transformers
 • 
Sheryl Bellary
Simplifying Similarity Problem: Introduction to Siamese Neural Networks
Learn how a machine learning model is created using few images per class.
 • 
Sheryl Bellary
A look at Stable Diffusion - An open-source text to image alternative to MidJourney and DALL-E 2
Implementing Stable Diffusion using Tensorflow and keras
 • 
Sheryl Bellary
Deep Dive into how Predicting Future Weights of Neural Network is used to mitigate Data Staleness while Distributed Training
Introducing SpecTrain as means to predict future weights of neural network to alleviate data staleness and improve speed of training via distributed…
 • 
Joshua Raj
1
Everything you need to know about Distributed training and its often untold nuances
Understanding Data Parallelism vs Model Parallelism, Their Powers and Their Kryptonite (weakness)
 • 
Joshua Raj
How to use Cyclical Learning Rate to get quick convergence for your Neural Network?
Achieve higher accuracy for your machine learning model in lesser iterations.
 • 
Sheryl Bellary
 and 
Priyanka Nath
How To Increase Recall When Given Imbalanced Dataset For Machine Learning Model?
SMOTE-Tomek Links is often suited for synthethic data generation when given imbalanced dataset.
 • 
Sheryl Bellary
Machine Learning Diaries
Machine Learning Diaries
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Machine Learning Diaries

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