▮ Learning Online While I was still learning about AI to become a data scientist as a residential architect, there was a lot of high-quality and free content on Youtube that helped me along the way. So for this post,…
▮ Data Shift After deploying your model, you’ll need to keep on maintaining them because data is constantly changing. So for this post, I’d like to share three different types of data distribution shifts that may occur which can degrade…
▮ Leakage Data leakage refers to the phenomenon when a form of a label “leaks” into the set of features used for making predictions even though this information is not available during inference in production. Data leakage is hard to…
▮ Low GPU Utilization Ideally, we want to use our GPU machines during training/inference fully. However, if you are not considering GPU utilization when creating training scripts for your deep learning model, the odds are that the GPU utilization rate…
▮ Stack Structure For this post, I’d like to share an intuitive overview of the basic steps of how your code communicates with the GPU when implementing deep learning models. Starting from the GPU side, the general process takes the…
▮ Learning How to Learn For this post, I’d like to share my top messages from the book “Make it stick” by Peter C Brown. I read 46 books last year, and this book about learning how to learn is…
▮ Sharing your findings In many cases, at the final phase of your data science project, you will need to organize and represent your findings to your audiences through a report as a deliverable. These reports can be in many…
▮ Where to Find When starting a new project, you may need additional data to train your machine-learning model. So for this post, I’d like to share a couple of resources that might be able to help you find more…
▮ Data The growth of data volume has been exponentially fast, especially these past few years. The plot below by Statista shows that the data volume this year(2023) has nearly doubled compared to 2020. However, despite the abundance of data…
▮ Elements Metric learning aims to measure the similarity between samples while using distance metrics for learning. Due to a survey in 2019, this field seems to become more and more important. So for this post, I’d like to share…