fast.ai

Fast.ai is a research institute that is dedicated to making deep learning and artificial intelligence more accessible to people from all walks of life. Founded by well-known data scientists and entrepreneurs Jeremy Howard and Dr. Rachel Thomas, Fast.ai provides a range of resources to help people learn about deep learning, regardless of their technical ability or education. With a focus on inclusivity and diversity in the tech industry, Fast.ai provides a free deep learning course, videos, code, datasets, and an active forum for people to learn and ask questions.

TLDR

Fast.ai is a research institute founded by renowned data scientists and entrepreneurs Jeremy Howard and Dr. Rachel Thomas that aims to make deep learning and artificial intelligence more accessible to everyone, regardless of their technical ability or educational background. Fast.ai provides a free deep learning course that covers everything from fundamental theory to advanced techniques, along with videos, code, datasets, and an active forum for learning and support. The company is committed to promoting inclusivity and diversity in the tech industry and offering practical, hands-on projects to supplement learning. Fast.ai's deep learning library provides high-level components for standard tasks and low-level components for innovative experimentation and research, while also being flexible and easy to use for new users. Fast.ai resources are free and open-source, available to anyone for personal or commercial use. Alternatives to Fast.ai include OpenAI, Coursera, TensorFlow, and Kaggle.

Company Overview

Fast.ai is a research institute dedicated to making deep learning more accessible to people from all backgrounds. They believe that everyone should be involved with artificial intelligence, regardless of their education or technical skills. The company is committed to making deep learning easier to use and promote inclusion and diversity in the industry.

The founders of the company, Jeremy Howard and Dr. Rachel Thomas are renowned data scientists, educators, and entrepreneurs. Howard was the founding CEO of Enlitic, the first company to use deep learning in medicine. He was also the President and Chief Scientist of the data science platform, Kaggle. Dr. Thomas was the founding director of the USF Center for Applied Data Ethics and was selected by Forbes as one of 20 Incredible Women in AI.

Fast.ai stands by the idea that being cool is the opposite of what they want for deep learning. Instead, they aim to create accessibility to the tech regardless of operating systems like Windows (used by the majority of the world) and datasets considered obscure. They want to include everyone with uncool languages like C# and backgrounds, even if they didn't go to prestigious universities like Stanford. The goal of the company is to promote inclusivity and diversity so that everyone can benefit from the world-changing technology of artificial intelligence.

Fast.ai provides various resources to make learning deep learning easy for everyone. They provide a free deep learning course that has everything someone needs to get started with deep learning regardless of their technical ability. The company also provides code, videos, datasets, and an active forum for people to learn and ask questions. They make sure to emphasize the importance of practical, hands-on projects to supplement their learning.

Fast.ai has received worldwide recognition for their efforts in making deep learning accessible to all. They have been featured in prestigious publications such as MIT Tech Review, Forbes, and The Economist. Dr. Thomas and Howard have been invited to speak about their work all over the world.

The company is steadfast in their dedication to democratizing artificial intelligence and making deep learning accessible to everyone. "Making deep learning accessible to all" is their motto, and they are committed to fulfilling this promise by providing free resources and promoting inclusivity in the tech industry.

Features

Accessible and Practical Deep Learning Course

Learn Deep Learning Regardless of Technical Ability

Fast.ai provides a free deep learning course that is accessible to everyone, regardless of their technical ability or prior experience with AI. The course covers everything from fundamental theory to advanced techniques and includes everything someone needs to get started with deep learning. The course uses practical, hands-on projects as the backbone of its teaching style, ensuring students leave with the skills necessary to apply deep learning in real-world settings.

Active Forum for Support and Community

Fast.ai's deep learning course includes an active forum where students can ask questions and receive guidance from both peers and experts in the field. This not only provides a community for people to connect with others, but it also ensures that students receive support when they need it throughout the learning experience.

Videos, Code, and Datasets for Supplementing Learning

Fast.ai provides a wealth of supplementary resources alongside their deep learning course to enhance the learning experience. This includes videos, code, and datasets that can be used to supplement and reinforce the concepts covered in the course. These resources ensure that students have access to all the tools necessary to master the art of deep learning.

Research Institute and Deep Learning Library

State-of-the-Art Components for Standard Deep Learning Tasks

Fast.ai's deep learning library provides practitioners with high-level components that can quickly and easily provide state-of-the-art solutions in traditionally challenging deep learning tasks such as image recognition and natural language processing. These components enable people to create high-quality applications with minimal effort, even if they are not deep learning experts.

Low-Level Components for Innovative Experimentation and Research

Fast.ai's deep learning library also provides researchers with low-level components that they can mix and match to create their own custom approaches to complex problems. This enables researchers to develop innovative solutions to problems that traditional deep learning libraries struggle with.

Flexible and Easy to Use, Even for New Users

Fast.ai's deep learning library is designed to be both flexible and easy to use, even for people who are new to deep learning. It has a simple API with a range of customizable parameters, making it easy for users to tailor their models to suit their specific needs.

Commitment to Inclusivity and Diversity in AI

Dedicated to Making Deep Learning Accessible to Everyone

Fast.ai is dedicated to democratizing artificial intelligence and making deep learning accessible to everyone, regardless of their education, skills, or background. They provide free resources and promote inclusivity in the tech industry, including support for operating systems like Windows and programming languages like C#. Their goal is to make sure everyone can benefit from the world-changing technology of AI, not just those who attended top universities or have extensive technical knowledge.

Focus on Practical and Hands-on Projects

Fast.ai believes that the best way to learn deep learning is through practical, hands-on projects that put theory into action. This approach not only provides a more engaging learning experience, but it also ensures that students have the skills necessary to apply deep learning in real-world settings. This focus on practical application and inclusion makes fast.ai stand out in the AI industry.

Industry Recognition for Efforts in Promoting Inclusivity and Accessibility

Fast.ai's commitment to inclusivity and accessibility has gained them worldwide recognition in the tech industry. They have been featured in prestigious publications like MIT Tech Review, Forbes, and The Economist. The founders, Dr. Rachel Thomas and Jeremy Howard, have been invited to speak about their work all around the world. The company's motto, "Making deep learning accessible to all," is not just a slogan, it is a commitment to making AI accessible to everyone.

Open-Source and Apache 2.0 License

Completely Free and Open to Use by Anyone

Fast.ai's deep learning library is completely free and open-source, which means anyone can use it for personal or commercial projects without any licensing fees. This allows users to explore deep learning without any financial barriers and enables businesses to innovate with AI without worrying about expensive licensing fees.

Hosted on GitHub and Licensed Under the Apache 2.0 License

Fast.ai's deep learning library is hosted on GitHub and licensed under the Apache 2.0 license. The license is permissive, which means users can use, distribute, and modify the library however they want, as long as they adhere to the terms of the license. The open-source nature of the library also enables collaboration and contribution from a community of developers, ensuring that the library is constantly evolving and improving.

Support for Popular Deep Learning Frameworks

Fast.ai's deep learning library supports popular deep learning frameworks like PyTorch and TensorFlow, enabling users to take advantage of the power of these frameworks with the simplicity and flexibility of fast.ai's library. This allows users to choose the framework that best suits their needs while still being able to reap the benefits of fast.ai's user-friendly high-level components.

FAQ

What is fast.ai?

Fast.ai is a research institute that aims to make deep learning easily accessible to individuals from all backgrounds, regardless of their technical ability or educational background. The company provides various resources such as a free deep learning course, code, videos, and datasets to help people learn and ask questions.

Who are the founders of Fast.ai?

The founders of Fast.ai are Jeremy Howard and Dr. Rachel Thomas, who are both renowned data scientists, educators, and entrepreneurs in the industry. Howard was the founding CEO of Enlitic, the first company to use deep learning in medicine, and President and Chief Scientist of data science platform Kaggle. Dr. Thomas was the founding director of the USF Center for Applied Data Ethics and was selected by Forbes as one of 20 Incredible Women in AI.

What is the goal of fast.ai?

The goal of Fast.ai is to promote inclusivity and diversity in the tech industry by making deep learning more accessible and easier to use. They provide free resources and emphasize the importance of practical, hands-on projects to supplement learning.

What resources does fast.ai provide?

Fast.ai provides a free deep learning course, code, videos, datasets, and an active forum for people to learn and ask questions. Their resources are open to everyone regardless of operating systems and programming languages.

How has fast.ai been recognized for their efforts?

Fast.ai has been recognized worldwide for their efforts in making deep learning more accessible. They have been featured in prestigious publications such as MIT Tech Review, Forbes, and The Economist. The founders have also been invited to speak about their work all over the world.

Alternatives

Looking for alternatives to fast.ai's deep learning and AI courses? Check out these top picks:

OpenAI

OpenAI is a research organization that aims to create AGI or Artificial General Intelligence. The group provides resources such as research papers and tools like GPT-3, a state-of-the-art language AI model that can generate text with incredible speed and accuracy.

Coursera

Coursera is an online education platform that offers a range of courses in various fields, including AI and deep learning. Courses are taught by distinguished professors from top universities and are designed to be accessible to anyone with an internet connection.

Tensorflow

TensorFlow is an open-source software library for machine learning and deep neural networks. Developed by Google Brain, TensorFlow has become one of the most popular tools for building and training machine learning models.

Kaggle

Kaggle is a community of data scientists and machine learning enthusiasts who come together to learn, compete, and collaborate. Kaggle offers many resources, including datasets, competitions, courses, and a vibrant community of data science enthusiasts.