fast.ai
fast.ai is a non-profit organization that provides free, practical deep learning courses and libraries to make AI more accessible and democratized.
https://www.fast.ai/
Product Information
Updated:May 16, 2025
fast.ai Monthly Traffic Trends
fast.ai experienced a 14.0% decline in traffic, reaching 417K visits. Without specific updates or activities from fast.ai in April 2025, the decline may be attributed to the broader market dynamics, including significant AI developments and updates from major players like Google.
What is fast.ai
fast.ai is a research company dedicated to making deep learning more accessible through free online courses, open-source software libraries, and cutting-edge research. Founded by Jeremy Howard and Rachel Thomas in 2016, fast.ai aims to empower people from diverse backgrounds to use deep learning and AI, even without extensive mathematical or coding experience. Their approach focuses on practical, hands-on learning using state-of-the-art techniques that are typically only available to experts.
Key Features of fast.ai
fast.ai is a deep learning library and educational platform that aims to make deep learning accessible to a wider audience. It provides high-level APIs built on PyTorch, practical courses and tutorials, and focuses on best practices in deep learning. fast.ai emphasizes a top-down teaching approach, starting with practical applications before diving into theory.
High-level deep learning API: Provides an intuitive interface for quickly building state-of-the-art deep learning models on top of PyTorch
Practical deep learning courses: Offers free online courses teaching deep learning through hands-on coding and real-world applications
Top-down teaching approach: Starts with working code and applications before explaining underlying theory and math
Focus on best practices: Incorporates latest research and industry best practices for training fast and accurate models
Emphasis on accessibility: Designed to be usable by people from diverse backgrounds, not just those with advanced math/CS degrees
Use Cases of fast.ai
Computer vision: Building image classification, object detection, and segmentation models for applications like medical imaging
Natural language processing: Creating models for tasks like sentiment analysis, text classification, and language generation
Tabular data analysis: Applying deep learning to structured data for predictive modeling and forecasting
Recommendation systems: Developing collaborative filtering models for personalized recommendations
Time series forecasting: Building models to predict future values based on historical time series data
Pros
Makes deep learning more accessible to beginners
Focuses on practical, real-world applications
Incorporates latest research and best practices
Provides free, high-quality educational resources
Cons
May abstract away some low-level details for advanced users
Primarily focused on PyTorch, less support for other frameworks
Course materials may become outdated as the field rapidly evolves
How to Use fast.ai
Set up a GPU-enabled environment: Use a cloud platform like Google Colab or set up a local environment with an NVIDIA GPU. Fast.ai recommends using Google Colab for beginners as it's free and easy to use.
Install the fastai library: If using Colab, run: !pip install fastai. For local installations, use conda or pip to install fastai and its dependencies.
Import the necessary modules: At the start of your notebook or script, import fastai modules: from fastai.vision.all import *
Load and prepare your data: Use fastai's DataBlock API to easily load and prepare your dataset for training.
Create a learner: Use fastai's cnn_learner or unet_learner to create a model with pre-trained weights.
Train the model: Use the fit or fit_one_cycle method to train your model on the prepared data.
Evaluate and fine-tune: Use fastai's interpretation tools to evaluate model performance and fine-tune as needed.
Make predictions: Use the trained model to make predictions on new data.
fast.ai FAQs
fast.ai is a non-profit research group focused on making deep learning more accessible. They provide free online courses, a deep learning library, and conduct research to democratize AI.
Official Posts
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Analytics of fast.ai Website
fast.ai Traffic & Rankings
417.3K
Monthly Visits
#112774
Global Rank
#3033
Category Rank
Traffic Trends: May 2024-Apr 2025
fast.ai User Insights
00:01:07
Avg. Visit Duration
2.32
Pages Per Visit
52.94%
User Bounce Rate
Top Regions of fast.ai
US: 19.23%
IN: 10.33%
CN: 3.84%
ES: 3.46%
GB: 3.39%
Others: 59.74%
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