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Momentum
In Section 12.4 we reviewed what happens when performing stochastic gradient descent, i.e., when performing optimization where only a noisy variant of the gradient is available. In particular, we noti...
Read more at Dive intro Deep Learning Book
Why Momentum Really Works
Here’s a popular story about momentum [1, 2, 3] : gradient descent is a man walking down a hill. He follows the steepest path downwards; his progress is slow, but steady. Momentum is a heavy ball rol...
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Why to Optimize with Momentum
Momentum optimiser and its advantages over Gradient Descent
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Momentum, Adam’s optimizer and more
If you’ve checked the jupyter notebook related to my article on learning rates, you’d know that it had an update function which was basically calculating the outputs, calculating the loss and…
Read more at Becoming Human: Artificial Intelligence Magazine
An Intuitive and Visual Demonstration of Momentum in Machine Learning
Speedup machine learning model training with little effort.
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Uncovering Momentum Effect with Rolling Intertemporal Analysis
The article demonstrates the intertemporal approach that extends and generalizes the scope of the rolling time series technique for deriving models of transition processes and empirical strategies…
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Momentum: A simple, yet efficient optimizing technique
What are gradient descent, moving average and how can they be applied to optimize Neural Networks? How is Momentum better than gradient Descent?
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Why 0.9? Towards Better Momentum Strategies in Deep Learning.
Momentum is a widely-used strategy for accelerating the convergence of gradient-based optimization techniques. Momentum was designed to speed up learning in directions of low curvature, without…
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👷♀️🧑🏻🎓👩💻👨🏻🏫 The MoE Momentum
📝 Editorial Massively large neural networks seem to be the pattern to follow these days in the deep learning space. The size and complexity of deep learning models are reaching unimaginable levels, p...
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Gradient Descent With Momentum
The problem with gradient descent is that the weight update at a moment (t) is governed by the learning rate and gradient at that moment only. It doesn’t take into account the past steps taken while…
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Stochastic Gradient Descent & Momentum Explanation
Let’s talk about stochastic gradient descent(SGD), which is probably the second most famous gradient descent method we’ve heard most about. As we know, the traditional gradient descent method…
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Is PyTorch’s Nesterov Momentum Implementation Wrong?
Momentum helps SGD traverse complex loss landscapes more efficiently. Photo by Maxim Berg on Unsplash. Introduction If you look closely at PyTorch’s documentation of SGD, you will find that their impl...
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Performance
Performance Whether exploring data in interactive mode or programmatically saving lots of plots, rendering performance can be a challenging bottleneck in your pipeline. Matplotlib provides multiple wa...
Read more at Matplotlib User's Guide
The Generative Audio Momentum
Next Week in The Sequence: Edge 303: Our series about new methods in generative AI continues with an exploration of different retrieval-augmented foundation model techniques. We discuss Meta AI’s famo...
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Beating the Odds
This is the first installment in my weekly sports themed series. Each week I’ll demonstrate applications of data science and seek to provide thoughtful analysis and insight into the games we love to…
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The Pursuit of Lift
TL; DR — Data Science teams pursue performance lift, but many ML projects failed. This article provides a framework to diagnose why that might have happened.
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Algorithmic Momentum Trading Strategy
Infusing Big Data + Machine Learning & Technical Indicators for a Robust Algorithmic Momentum Trading Strategy Big data is completely revolutionizing how the stock markets across the world are…
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Optimizers — Momentum and Nesterov momentum algorithms (Part 2)
Welcome to the second part on optimisers where we will be discussing momentum and Nesterov accelerated gradient. If you want a quick review of vanilla gradient descent algorithms and its variants…
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Creating Impact
In some large tech companies, Data Scientists are evaluated by how much impact they make in the company. For example, if a Data Science employee created an algorithm to predict the year’s revenue…
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A Dive into Dash
Around my office job, there are have been several discussions about the inclusion of dashboards. Typically, we used them to represent data to our business users, but with the new system, it was…
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Stop Using Velocity To Measure Your Teams — Try These Metrics Instead
Metrics without context are a waste of time. Continue reading on Better Programming
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Metaphysics
So far, we’ve been talking about objects: what they are, how they behave, methods and attributes, descriptors, context management and creation. All objects are defined in classes, so we’ve been…
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Move fast and break stuff
Photo by mpiresI recently talked to someone at a very innovative large web company (under Frie-NDA) who described their official engineering motto as "Move fast and break stuff". I love that philosoph...
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Anatomy of Cricket Analytics
How everyone will try to control the flow of the ball in a game and those who did it better during the game will always win. A four-letter word has profoundly put impact in the sporting world; when…
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