A collection of lectures on deep learning, deep reinforcement learning, autonomous vehicles, and artificial intelligence organized by Lex Fridman.

In our technical deep-dive blog, we discuss some essential Natural Language Processing (NLP) tools and techniques for improving query understanding. But not all NLP projects are feasible within a reasonable cost and time. After having done numerous NLP projects…

Pete Skomoroch’s session provides a “crash course” on what product managers and leaders need to know about shipping AI projects.

This is the Plato Research Dialogue System, a flexible platform for developing conversational AI agents. - uber-archive/plato-research-dialogue-system

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - GitHub - huggingface/t...

The Data Engineering Cookbook. Contribute to andkret/Cookbook development by creating an account on GitHub.

Facebook is open-sourcing DLRM, a deep learning-based recommendation model that achieves state-of-the-art results in personalization.

Whether large or small, almost every organisation is looking for aspiring data scientists who will not only help them churn out meaningful insights from

There is more to building a sustainable Deep Learning solution than what is provided by Deep Learning frameworks like TensorFlow and…

Docker is everywhere in the software industry today. We will take a look at how docker in helping in the Machine Learning spectrum.

Using Flask to deploy an ML model

Generative Adversarial Networks, or GANs, are an architecture for training generative models, such as deep convolutional neural networks for generating images. The conditional generative adversarial network, or cGAN for short, is a type of GAN that involves…