fast.ai


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Tags Whois Rank Speed Safety Headers Similar Sites Keywords H Tags

fast.ai Website Info

fast.ai (Fast.ai is an organization dedicated to making deep learning accessible and practical for everyone. They provide free online courses, tutorials, and open-source libraries designed to enable developers and researchers to create state-of-the-art AI applications quickly and effectively. Their approach emphasizes practical implementation and real-world impact in the field of artificial intelligence.) DNS looks Active and website looks Accessable. There is also a page about the fast.ai on Wikipedia.fast.ai Website SEMRush Rank is 128,919. fast.ai seems popular on facebook. According to Google, website speed score is 90/100 and AVERAGE. Website looks safe for children. We detected the website language as en.
fast.ai


fast.ai Website Tags

Domain Status:
✓ Active
Is Site Accessable?:
✓ Yes
SSL(https):
✓ Yes
Accessable Url:
https://www.fast.ai
Title:
fast.ai—Making neural nets uncool again – fast.ai
Description:
Fast.ai offers practical deep learning courses and libraries to help developers and researchers build intelligent applications efficiently. Accessible, free, and beginner-friendly.
Wiki:
Nonprofit research group fast.ai is a non-profit research group focused on deep learning and artificial intelligence. It was founded in 2016 by Jeremy Howard and Rachel Thomas with the goal of democratizing deep learning. They do this by providing a massive open online course (MOOC) named "Practical Deep Learning for Coders," which has no other prerequisites except for knowledge of the programming language Python. https://en.wikipedia.org/wiki/Fast.ai
Categories :
Technical/Business Forums, Information Technology
External Links:
6
Internal Links:
4
Mobile Friendly?:
No
USE_LEGIBLE_FONT_SIZES
TAP_TARGETS_TOO_CLOSE
SIZE_CONTENT_TO_VIEWPORT
Canonical URL:
[Not Set]
Language:
en
XML Sitemap:
✗ No
robots.txt:
✓ Yes https://www.fast.ai/robots.txt
Favicon:
✗ No

fast.ai Domain & Whois Details

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Server Type:
GitHub.com
Hosting Location:
Country: United States (US) /
Location:
ISP:
IP:
185.199.110.153 , 185.199.109.153 , 185.199.108.15

fast.ai Backlinks & Rankings

SEMRush Rank:
128,919
Semrush Rank is a proprietary score that lets you find the domains that are getting the most traffic from organic search.
SEMRush Traffic:
14,364
Number of users expected to visit the website during the following month.
SEMRush Costs:
26,626
Estimated price of organic keywords in Google AdWords.
SEMRush URL Links:
9,160
Number of links to URL according to SemRush.
SEMRush Website Links:
13,743
Number of links to the website according to SemRush.
SEMRush Domain Links:
312,798
Number of links to SemRush Domain.
SEMRush Keywords In Top 100:
26,455
Number of keywords where site in Google's organic search top 100.

fast.ai Social Media

Facebook Comments:
540
Facebook Shares:
1,237
Facebook Reactions:
1,507

fast.ai Website Speed (Desktop)

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Overall Category:
AVERAGE
The human readable speed "category"
Speed Index:
90
Speed Index shows how quickly the contents of a page are visibly populated. [Learn more about the Speed Index metric].
Cumulative Layout Shift (CLS):
0.01 (FAST)
The Cumulative Layout Shift (CLS) metric measures how much unexpected layout shifts affect the user experience on a page. These layout shifts occur when content moves around without prior user input. CLS
Time to First Byte (TTFB):
0.653 s (FAST)
TTFB (time to first byte) is the number of milliseconds it takes for a client’s browser to receive the first byte of the response from the web server. Usually, TTFB can be improved with faster hosting and server optimizations. TTFB
First Input Delay (FID):
3 ms (FAST)
First Input Delay (FID) measures the time from when the user interacts with your site for the first time (click a link, tap on a button, etc.) to the time when the browser is able to respond to that interaction. Google recommends keeping FID below 100ms for a good user experience. FID
First Contentful Paint (FCP):
1.818 s (AVERAGE)
FCP (First Contentful Paint) measures the time from a user’s navigation to when the browser renders the first bit of content from the DOM. In other words, FCP marks the time at which the first text or image is painted for the user. According to PageSpeed Insights, FCP should occur in under 2 seconds. FCP
Interaction to Next Paint (INP):
20 ms (FAST)
Interaction to Next Paint (INP) is a web performance metric that measures user interface responsiveness – how quickly a website responds to user interactions like clicks or key presses. Specifically, it measures how much time elapses between a user interaction like a click or key press and the next time the user sees a visual update on the page. INP
Largest Contentful Paint (LCP):
2.134 s (FAST)
Largest Contentful Paint (LCP) is a metric that measures when the largest content in the viewport is rendered. It is used to measure how long it takes for the main content of your webpage to appear on the screen. Everything below 2.5s is considered good LCP time by PageSpeed Insights. LCP
Total Size:
5449 KB
Total Size. Large network payloads cost users real money and are highly correlated with long load times.
Server Response Time:
102 ms
Initial server response time. Keep the server response time for the main document short because all other requests depend on it. [Learn more about the Time to First Byte metric](https://developer.chrome.com/docs/lighthouse/performance/time-to-first-byte/).
Final Url:
https://www.fast.ai/
Canonicalized and final URL for the document, after following page redirects (if any).
Last Date Checked:
5/22/2023 10:14:46 AM
The last time we checked this website.
Site Speed Check(Full)

fast.ai HTML Resources

Type
Request Count
Size
Total
51
5,449 KB
Image
22
4,702 KB
Third-party
7
440 KB
Script
16
401 KB
Font
3
249 KB
Stylesheet
6
64 KB
Document
1
29 KB
Other
3
2 KB
Media
0
0 KB

fast.ai Website Safety

Refresh
Last Check Date:
2/23/2023 6:19:08 AM
Fortiguard:
Information Technology
Mcafee Category:
Technical/Business Forums
OpenDNS:
BeFirst
Cloudflare DNS:
OK
MyWot Child Safety:
99

fast.ai HTTP Headers

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Cache-Control :
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expires :
Wed, 10 May 2023 01:53:18 GMT
Last-Modified :
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Via :
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X-Proxy-Cache :
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X-Timer :
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fast.ai W3C HTML Validation Check Now

Last Check Date:
5/27/2023 12:00:00 AM
Errors:
548
Warnings:
0
Info:
3
Check Live:
Check fast.ai HTML Errors

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Top fast.ai Alternatives

fast.ai Site Keywords

ARTIFICIAL INTELLIGENCE
automl
deep learning
fast ai
fast.ai—Making neural nets uncool again
fastai
free resources
jeremy howard
keras
log loss
machine learning
Making neural nets uncool again
neural networks
Online Courses

fast.ai Site H Tags

Check Now
h1
fast.ai—Making neural nets uncool again
h3
Blog
h3
Is Avoiding Extinction from AI Really an Urgent Priority?
h3
Mojo may be the biggest programming language advance in decades
h3
From Deep Learning Foundations to Stable Diffusion
h3
GPT 4 and the Uncharted Territories of Language
h3
I was an AI researcher. Now, I am an immunology student.
h3
1st Two Lessons of From Deep Learning Foundations to Stable Diffusion
h3
Deep Learning Foundations Signup, Open Source Scholarships, & More
h3
From Deep Learning Foundations to Stable Diffusion
h3
My family’s unlikely homeschooling journey
h3
The Jupyter+git problem is now solved
h3
nbdev+Quarto: A new secret weapon for productivity
h3
Practical Deep Learning for Coders 2022
h3
Masks for COVID: Updating the evidence
h3
Qualitative humanities research is crucial to AI
h3
AI Harms are Societal, Not Just Individual
h3
There’s no such thing as not a math person
h3
7 Great Lightning Talks Related to Data Science Ethics
h3
Doing Data Science for Social Good, Responsibly
h3
Avoiding Data Disasters
h3
SARS-CoV-2 Spike Protein Impairment of Endothelial Function Does Not Impact Vaccine Safety
h3
Statistical problems found when studying Long Covid in kids
h3
Medicine is Political
h3
Inaccuracies, irresponsible coverage, and conflicts of interest in The New Yorker
h3
Australia can, and must, get R under 1.0
h3
11 Short Videos About AI Ethics
h3
Getting Specific about AI Risks (an AI Taxonomy)
h3
fastai A Layered API for Deep Learning
h3
fastdownload: the magic behind one of the famous 4 lines of code
h3
Is GitHub Copilot a blessing, or a curse?
h3
fastchan, a new conda mini-distribution
h3
20 Years of Tech Startup Experiences in One Hour
h3
I violated a code of conduct
h3
Avoiding the smoke - how to breath clean air
h3
fast.ai releases new deep learning course, four libraries, and 600-page book
h3
Forward from the ‘Deep Learning for Coders’ Book
h3
Applied Data Ethics, a new free course, is essential for all working in tech
h3
Essential Work-From-Home Advice: Cheap and Easy Ergonomic Setups
h3
Cloth masks can protect the wearer
h3
Particle sizes for mask filtration
h3
Introducing the first cohort of USF CADE Data Ethics Research Fellows
h3
Masks - FAQ for Skeptics
h3
Masks for all? The science says yes.
h3
6 Important Videos about Tech, Ethics, Policy, and Government
h3
Saving The Mask
h3
Covid-19, your community, and you - a data science perspective
h3
Disinformation: what it is, why it’s pervasive, and proposed regulations
h3
Tech Ethics Crisis: The Big Picture, and How We Got Here
h3
4 Principles for Responsible Government Use of Technology
h3
Blogging with Jupyter Notebooks
h3
Your own blog with GitHub Pages and fast_template (4 part tutorial)
h3
Blogging with screenshots
h3
Syncing your blog with your PC, and using your word processor
h3
Your own hosted blog, the easy, free, open way (even if you’re not a computer expert)
h3
Self-supervised learning and computer vision
h3
Data project checklist
h3
nbdev: use Jupyter Notebooks for everything
h3
Concerned about the impacts of data misuse? Ways to get involved with the USF Center for Applied Dat
h3
The problem with metrics is a big problem for AI
h3
8 Things You Need to Know about Surveillance
h3
Make Delegation Work in Python
h3
USF Launches New Center of Applied Data Ethics
h3
new fast.ai course: A Code-First Introduction to Natural Language Processing
h3
Deep Learning from the Foundations
h3
A LaTeX add-in for PowerPoint - my father’s day project
h3
Was this Google Executive deeply misinformed or lying in the New York Times?
h3
Advice for Better Blog Posts
h3
Decrappification, DeOldification, and Super Resolution
h3
16 Things You Can Do to Make Tech More Ethical, part 3
h3
16 Things You Can Do to Make Tech More Ethical, part 2
h3
16 Things You Can Do to Make Tech More Ethical, part 1
h3
fast.ai Embracing Swift for Deep Learning
h3
A Conversation about Tech Ethics with the New York Times Chief Data Scientist
h3
Dairy farming, solar panels, and diagnosing Parkinson’s disease: what can you do with deep learning?
h3
fastec2 script: Running and monitoring long-running tasks
h3
Some thoughts on zero-day threats in AI, and OpenAI’s GPT-2
h3
fastec2: AWS computer management for regular folks
h3
Five Things That Scare Me About AI
h3
fast.ai Diversity Fellows and Sponsors Wanted
h3
Practical Deep Learning for Coders 2019
h3
C++11, random distributions, and Swift
h3
High Performance Numeric Programming with Swift: Explorations and Reflections
h3
One year of deep learning
h3
The new fast.ai research datasets collection, on AWS Open Data
h3
fastai v1 for PyTorch: Fast and accurate neural nets using modern best practices
h3
Introduction to Machine Learning for Coders: Launch
h3
AI Ethics Resources
h3
What You Need to Know Before Considering a PhD
h3
Practical Deep Learning for Coders, part-time Diversity Fellowships, Fall 2018
h3
Now anyone can train Imagenet in 18 minutes
h3
What HBR Gets Wrong About Algorithms and Bias
h3
Google’s AutoML: Cutting Through the Hype
h3
An Opinionated Introduction to AutoML and Neural Architecture Search
h3
What do machine learning practitioners actually do?
h3
AdamW and Super-convergence is now the fastest way to train neural nets
h3
Launching Cutting Edge Deep Learning for Coders: 2018 edition
h3
Training Imagenet in 3 hours for USD 25; and CIFAR10 for USD 0.26
h3
An Introduction to Deep Learning for Tabular Data
h3
What you need to know about Facebook and Ethics
h3
A Discussion about Accessibility in AI at Stanford
h3
Adding Data Science to your College Curriculum
h3
Practical Deep Learning for Coders 2018
h3
International Fellowship applications for Part 2 now open
h3
New Opportunities For New Deep Learning Practitioners
h3
Five Trends to Avoid When Founding a Startup
h3
Deep Learning Diversity Fellowship Applications Now Open
h3
Making Peace with Personal Branding
h3
What you need to do deep learning
h3
How (and why) to create a good validation set
h3
When Data Science Destabilizes Democracy and Facilitates Genocide
h3
Credible sources of accurate information about AI
h3
Can Neural Nets Detect Sexual Orientation? A Data Scientist’s Perspective
h3
Introducing Pytorch for fast.ai
h3
International Fellowship applications for Part 1 now open
h3
Notes on state of the art techniques for language modeling
h3
Advice to Medical Experts Interested in AI
h3
Sponsor a Deep Learning Diversity Scholarship
h3
Diversity Crisis in AI, 2017 edition
h3
Announcing fast.ai diversity scholarships
h3
Thoughts on OpenAI, reinforcement learning, and killer robots
h3
Cutting Edge Deep Learning for Coders: Launching Deep Learning Part 2
h3
New fast.ai course: Computational Linear Algebra
h3
How to Encourage Your Child’s Interest in Science and Tech
h3
Alternatives to a Degree to Prove Yourself in Deep Learning
h3
To become a data scientist, focus on coding
h3
Machine learning hasn’t been commoditized yet, but that doesn’t mean you need a PhD
h3
How to change careers and become a data scientist - one quant’s experience
h3
Deep Learning: Not Just for Silicon Valley
h3
Deep Learning For Coders - Full notes and transcripts now available
h3
Diversity and International Fellowships for Deep Learning Part 2
h3
Practical Deep Learning Part 2 - Integrating Recent Advances and Classic Machine Learning
h3
Big deep learning news: Google Tensorflow chooses Keras
h3
Where is AI/ML actually adding value at your company?
h3
The Deep Learning MOOC is now available!
h3
(Update - problem resolved!) Azure and AWS’s ‘GPU general availability’ lies
h3
So you are interested in deep learning
h3
How should you structure your Data Science and Engineering teams?
h3
It used to be called big data and now it’s called deep learning
h3
Additional Diversity Fellowship, New International Fellowships, and Deadline Extended to 10/17
h3
New Electricity
h3
The Diversity Crisis in AI, and fast.ai Diversity Fellowship
h3
What We Will Cover in the First Deep Learning Certificate
h3
Providing a Good Education in Deep Learning
h3
A unique path to deep learning expertise
h3
The First Certificate in Deep Learning
h3
Launching fast.ai
h5
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