The key to unlocking the power of machine learning (ML) lies in having high-quality labeled data. In this email, we’ll explore the significance of labeled data, its impact on the performance of ML models, and how you can capitalize on this natural resource of the modern age to drive your … Read more
As you think through the ways machine learning (ML) can be used to accelerate your business, it can be helpful to see how other companies have done it. Today, I want to share an example of how General Electric (GE) harnessed the power of ML to transform a large part … Read more
Machine learning has revolutionized the world of technology, playing a crucial role in various applications, from self-driving cars and facial recognition systems to language translation and sentiment analysis. The success of machine learning models largely depends on the quality and quantity of data they are trained on. In particular, labeled … Read more
As an entrepreneur looking to harness the power of machine learning (ML) in your business, understanding the data science process is crucial. This process can be broken down into three main steps: The goal is to move through these stages as quickly as possible so that you can gather feedback … Read more
How do utility companies monitor thousands of miles of electrical wire to find small imperfections that threaten the entire system? For the entire history of electrical infrastructure, the only answer has been ‘very slowly.’ Now, Sparrow’s computer vision capabilities, combined with Fast Forward’s thermal imaging system, can accomplish what used … Read more
Overview This post is going to showcase the development of a vehicle speed detector using Sparrow Computing’s open-source libraries and PyTorch Lightning. The exciting news here is that we could make this speed detector for any traffic feed without prior knowledge about the site (no calibration required), or specialized imaging … Read more
The TorchVision datasets subpackage is a convenient utility for accessing well-known public image and video datasets. You can use these tools to start training new computer vision models very quickly. TorchVision Datasets Example To get started, all you have to do is import one of the Dataset classes. Then, instantiate … Read more
The np.any() function tests whether any element in a NumPy array evaluates to true: The input can have any shape and the data type does not have to be boolean (as long as it’s truthy). If none of the elements evaluate to true, the function returns false: Passing in a … Read more
PyTorch comes with powerful data loading capabilities out of the box. But with great power comes great responsibility and that makes data loading in PyTorch a fairly advanced topic. One of the best ways to learn advanced topics is to start with the happy path. Then add complexity when you … Read more
Understanding the np.append() operation and when you might want to use it.