The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices around the world, where the IoT devices collect and share information to reflect status of the physical ...

Deep learning has achieved remarkable success in numerous domains with help from large amounts of big data. However, the quality of data labels is a concern because of the lack of high-quality labels ...

In this repository there are a number of tutorials in Jupyter notebooks that have step-by-step instructions on how to deploy a pretrained deep learning model on a GPU enabled Kubernetes cluster. The ...

Companies desperately need AI talent across all industries, not just technology firms that beginners mistakenly think dominate hiring.Structured l ...

This project explores how Reinforcement Learning (RL)—specifically, Deep Q-Learning—can be used to develop algorithmic trading strategies. We simulate a trading agent that learns to make buy, sell, ...

Python is the most widely used programming language for data science. It’s simple, easy to understand, and clean. GitHub states that over 80% of data science projects used Python last year. It has ...

Super useful for keeping things organized. Let’s get into it. Harnessing Pre-installed Python Libraries in Google Colab Google Colab is ready to roll with a ton of pre-installed Python libraries, ...

This book may be of interest to Gadget Masters getting serious with the use of AI and looking to develop their own learning model. It's called Practical Deep Learning. Or Practical Deep Learning (2nd ...

A new machine learning approach that draws inspiration from the way the human brain seems to model and learn about the world has proven capable of mastering a number of simple video games with ...

Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code remains underexplored. Due to the size and complexities of ...