Building a Production-Level Data Pipeline Using Kedro
How can Kedro help you? Suppose you are a self-taught data scientist who does not have much experience in software development. One morning, your senior executive asks you to provide an ad-hoc analysis – perks of the job, and when you do, she thanks you for... Read more
10 Compelling Machine Learning Ph.D. Dissertations for 2020
As a data scientist, an integral part of my work in the field revolves around keeping current with research coming out of academia. I frequently scour arXiv.org for late-breaking papers that show trends and reveal fertile areas of research. Other sources of valuable research developments are... Read more
An Intro to Gradual Magnitude Pruning (GMP)
Welcome to Part 2 in Neural Magic’s five-part blog series on pruning in machine learning. In case you missed it, Part 1 gave a pruning overview, detailed the difference between structured vs. unstructured pruning, and described commonly used algorithms, including Gradual Magnitude Pruning (GMP). Few algorithms are... Read more
How to Explain Your ML Models?
Explainability in machine learning (ML) and artificial intelligence (AI) is becoming increasingly important. With the increased demand for explanations and the number of new approaches out there, it could be difficult to know where to start. In this post, we will get hands-on experience in explaining... Read more
Intro to Vectors and Matrices in Machine Learning
Programming is a great way to get insights about math concepts. You’ll see here tips and tricks to learn math, more specifically linear algebra, from a coding perspective. You’ll see the relationship between Numpy functions and linear algebra abstract concepts. At the end of this mini-tutorial,... Read more
Autograd is PyTorch’s automatic differentiation package. Thanks to it, we don’t need to worry about partial derivatives, chain rule, or anything like it. To illustrate how it works, let’s say we’re trying to fit a simple linear regression with a single feature x, using Mean Squared... Read more
Continuous Delivery for Machine Learning
Why is bringing machine learning code into production hard? Machine Learning applications are becoming popular in all industries. However, the process for developing, deploying, and continuously improving them is more complex compared to more traditional software, such as a web service or a mobile application. These... Read more
What is Pruning in Machine Learning?
So what is pruning in machine learning? Pruning is an older concept in the deep learning field, dating back to Yann LeCun’s 1990 paper Optimal Brain Damage. It has recently gained a lot of renewed interest, becoming an increasingly important tool for data scientists. The ability... Read more
Reinforcement Learning with Ray RLlib
Why Reinforcement Learning? In reinforcement learning (RL), an agent tries to maximize a reward while interacting with an environment. The agent observes the state of the environment, takes an action and observes the reward received (if any) and the new state. Then the agent takes the... Read more
Best Practices for Dealing with Concept Drift
You trained a machine learning model, validated its performance across several metrics which are looking good, you put it in production, and then something unforeseen happened (a pandemic like COVID-19 arrived) and the model predictions have gone crazy. Wondering what happened? You fell victim to a... Read more