Depth estimation in videos plays a key role in many modern applications, from self-driving cars to augmented reality. The “Depth Any Video” model, developed by researchers Honghui Yang, Di Huang, Wei Yin, Chunhua Shen, Haifeng Liu, Xiaofei He, Binbin Lin,…
Today, we’re diving into the fascinating world of Retrieval-Augmented Generation, commonly known as RAG, in deep learning. This isn’t just another tech buzzword; it’s a groundbreaking concept reshaping how AI systems understand and interact with the world around them. Think…
In this article, we’ll look at what quantization is and how you can use it with TensorFlow to improve and accelerate your models. Since the release of ChatGPT, researchers have been striving to shrink the ever-growing storage space used by…
In this article, I’ll show you how to use a Random Seed with TensorFlow to achieve reproducible results with your model. Unlike traditional Machine Learning, training a Deep Learning model is a highly complex process. In this process is used…
In this article, I unveil the secrets of Bayesian Optimization, a revolutionary technique for optimizing hyperparameters. Hyperparameters play an essential role in the performance of Machine Learning models. However, finding the optimal combination of hyperparameters can be a daunting task.…
In this article, you’ll discover 3 ways to open a Parquet file in Python to load your data into your environment. As a Data Scientist, it’s essential to learn how to open a Parquet file in Python. This file format,…