DeepLearning

Pre-trained models are making waves in the deep learning world. Using massive pre-training datasets, these NLP models bring previously unheard-of feats of AI within the reach of app developers.

Unwanted AI bias is already a widespread problem. Machine learning models can replicate or exacerbate existing biases, often in ways that are not detected until release. So what can be done about it?

Manually gathering information about user-generated data is time-consuming, to say the least. That’s why more organizations are turning to automatic sentiment analysis methods—but basic models don’t always cut it. In this article, Toptal Freelance Data Scientist Rudolf Eremyan gives an overview of some sentiment analysis gotchas and what can be done to address them.

Leveraging DeepMind’s breakthrough AI approaches takes some work, but the results are astounding. In this article, Toptal Freelance Deep Learning Engineer Neven Pičuljan guides us through the building blocks of reinforcement learning, training a neural network to play Flappy Bird using the PyTorch framework.

In this article, Toptal Freelance Software Engineer Neven Pičuljan introduces you to the intricacies of deep learning in hedge funds and finance in general.

TensorFlow makes implementing deep learning on a production scale a breeze. However, understanding its core mechanisms and how dataflow graphs work is an essential step in leveraging the tool’s power.

In this article, Toptal Freelance Software Engineer Oliver Holloway demonstrates how TensorFlow works by first solving a general numerical problem and then a deep learning problem.

The recent resurgence in Artificial Intelligence has been powered in no small part by a new trend in machine learning, known as “Deep Learning”. In this article, I’ll introduce you to the key concepts and algorithms behind Deep Learning, beginning with the simplest building block.