Embracing Distributed Federated Learning for Scalable Business Solutions
The world of machine learning has seen rapid advancements in recent years, leading to the widespread adoption of ML models across various industries. One key development in this domain is distributed federated learning, a decentralized approach that facilitates the efficient training and application of ML models at scale. In this blog, we will discuss the importance of distributed federated learning for businesses and its potential to revolutionize the way industries leverage ML models....
Fine-Tuning a Pre-Trained ResNet-18 Model for Image Classification with PyTorch
Fine-tuning a pre-trained model for an image classification task on a domain-specific problem can significantly reduce the time and computational resources required for training a deep neural network from scratch. In this tutorial, I will walk through the steps of fine-tuning a pre-trained ResNet-18 model on a custom dataset using PyTorch. Step 1: Load the pre-trained model let’s start by loading the pre-trained ResNet-18 model from the PyTorch model zoo. The PyTorch model zoo provides a collection of pre-trained models that can be used for various computer vision tasks....
Continuous Delivery Champions
Photo by Nicolas Hoizey Modern software engineering is all about shipping fast and often It was about a month ago that I was introduced to a book called Accelerate and later discovered another study Accelerate State of DevOps Report. It is all natural to agile teams today but what all these studies demonstrate is that engineering teams that deliver more often are more likely to meet or exceed their organizational performance goals....
Key Components of An Effective Data Science Manager
Photo by Matteo Vistocco The role of the data science manager is to provide group-based leadership with a data science focus. The data science manager must have a deep understanding of the data science process and the ability to lead and motivate data science teams. The data science manager must also work with business stakeholders to understand their needs and translate them into data science solutions. The data science manager is responsible for the following:...
Three Aspects of Recommender Systems in Production
Recommender systems are everywhere. They are helpful but sometimes biased. But building a recommender system which is for sure an application of machine learning in production requires some special treatments and aspects to cover in comparison to other machine learning application like let’s say classification. In this article I will go through three of these aspects: Photo by Javier Allegue Barros 1. Model Selection How do you choose the model?...