In the previous chapter, we learned various strategies to guide AI models 'down the mountain' (optimization algorithms), such ...

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural ...

LSE students Adriana Svitkova and Idil Balci consider the core dangers that may arise as facial recognition software becomes a key component of our everyday lives. The LSE Data Science Institute (DSI) ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Nearly 50 new cancer therapies are approved every year. This is good news. "But for patients and their treating physicians, ...

Deep learning models, particularly Convolutional Neural Networks (CNN), are the core technologies for current Chinese handwriting recognition. The workflow can be summarized in the following steps: ...

Deep learning has advanced rapidly, driving breakthroughs in image recognition, natural language processing, and autonomous ...

Machine learning algorithms have been used to predict cancer progression, identify early signs of Parkinson’s disease, and ...