evjang.com

Evaluation du site evjang.com

Eric Jang | Personal website and blog of Eric Jang.

 Généré le 01 Avril 2026 14:07

Vieilles statistiques? UPDATE !

Le score est de 64/100

Optimisation du contenu

Titre

Eric Jang | Personal website and blog of Eric Jang.

Longueur : 51

Parfait, votre titre contient entre 10 et 70 caractères.

Description

Personal website and blog of Eric Jang.

Longueur : 39

Idéalement, votre balise META description devrait contenir entre 70 et 160 caractères (espaces compris). Utilisez cet outil gratuit pour calculer la longueur du texte.

Mots-clefs

Très mauvais. Nous n'avons pas trouvé de balise META keywords sur votre page. Utilisez ce générateur gratuit de balises META en ligne pour créer des mots-clés.

Propriétés Open Graph

Bien, cette page profite des balises META Open Graph.

Propriété Contenu
title Eric Jang
locale en_US
description Personal website and blog of Eric Jang.
url https://evjang.com/
site_name Eric Jang
type website

Niveaux de titre

H1 H2 H3 H4 H5 H6
0 1 59 0 0 0
  • [H2] Posts
  • [H3] As Rocks May Think
  • [H3] Leaving 1X
  • [H3] Ultra Instinct
  • [H3] Motor Physics
  • [H3] Questions about ARC Prize
  • [H3] All Roads Lead to Robotics
  • [H3] Takeaways from DeepMind's RoboCat Paper
  • [H3] Can LLMs Critique and Iterate on Their Own Outputs?
  • [H3] How Can We Make Robotics More like Generative Modeling?
  • [H3] All Roads Lead to Rome: The Machine Learning Job Market in 2022
  • [H3] Haikus about Effective Altruism
  • [H3] Ranking YC Companies with a Neural Net
  • [H3] Leaving Google Brain ✌️
  • [H3] To Understand Language is to Understand Generalization
  • [H3] Just Ask for Generalization
  • [H3] Robots Must Be Ephemeralized
  • [H3] ML Mentorship: Some Q/A about RL
  • [H3] Stonks are What You Can Get Away With
  • [H3] Sovereign Arcade: Currency as High-Margin Infrastructure
  • [H3] Science and Engineering for Learned Robots
  • [H3] Don't Mess with Backprop: Doubts about Biologically Plausible Deep Learning
  • [H3] How to Understand ML Papers Quickly
  • [H3] Software and Hardware for General Robots
  • [H3] My Criteria for Reviewing Papers
  • [H3] Chaos and Randomness
  • [H3] Free Office Hours for Non-Traditional ML Researchers
  • [H3] Three Questions that Keep Me Up at Night
  • [H3] Selected Quotes from "The Dark Ages of AI Panel Discussion" (1984)
  • [H3] Differentiable Path Tracing on the GPU/TPU
  • [H3] Robinhood, Leverage, and Lemonade
  • [H3] Tips for Training Likelihood Models
  • [H3] Normalizing Flows in 100 Lines of JAX
  • [H3] Lessons from AI Research Projects: The First 3 Years
  • [H3] Fun with Snapchat's Gender Swapping Filter
  • [H3] What I Cannot Control, I Do not Understand
  • [H3] Meta-Learning in 50 Lines of JAX
  • [H3] Thoughts on the BagNet Paper
  • [H3] Uncertainty: A Tutorial
  • [H3] Dijkstra's, in Disguise
  • [H3] Bots and Thoughts from ICRA2018
  • [H3] Aesthetically Pleasing Learning Rates
  • [H3] Teacup: A Short Story
  • [H3] Doing a Concurrent Masters at Brown
  • [H3] Normalizing Flows Tutorial, Part 2: Modern Normalizing Flows
  • [H3] Normalizing Flows Tutorial, Part 1: Distributions and Determinants
  • [H3] Gamma Correction
  • [H3] Expressivity, Trainability, and Generalization in Machine Learning
  • [H3] Strong AI Ideas in Crystal Nights (Greg Egan, 2009)
  • [H3] Summary of NIPS 2016
  • [H3] Tutorial: Categorical Variational Autoencoders using Gumbel-Softmax
  • [H3] How Can a Deep Neural Network with ReLU Activations Approximate any Function?
  • [H3] Riemann Summation and Physics Simulation are Statistically Biased
  • [H3] Monte Carlo Variance Reduction Techniques in Julia
  • [H3] A Beginner's Guide to Variational Methods: Mean-Field Approximation
  • [H3] Adversarial Exploration Policies for Robust Model Learning
  • [H3] Understanding and Implementing Deepmind's DRAW Model
  • [H3] Generative Adversarial Nets in TensorFlow: Part I
  • [H3] My Internship Experiences at Pixar, Google, and Two Sigma
  • [H3] Reverse-Engineering Apps: a Step-by-Step Beginner's Guide

Images

Nous avons trouvé 0 image(s) sur cette page Web.

Bien, la plupart ou la totalité de vos images possèdent un attribut alt

Ratio texte/HTML

Ratio : 19%

Bien, le ratio de cette page texte/HTML est supérieur à 15, mais inférieur à 25 pour cent.

Flash

Parfait, aucun contenu FLASH n'a été détecté sur cette page.

Iframe

Génial, il n'y a pas d'Iframes détectés sur cette page.

Réécriture d'URLs

Bien. Vos liens sont optimisés!

Tiret bas dans les URLs

Parfait! Aucuns soulignements détectés dans vos URLs.

Liens dans la page

Nous avons trouvé un total de 65 lien(s) dont 0 lien(s) vers des fichiers

Texte d'ancre Type Juice
Eric Jang Interne Passing Juice
Book: AI is Good for You Interne Passing Juice
Projects Interne Passing Juice
About Interne Passing Juice
Talks Interne Passing Juice
via RSS Interne Passing Juice
As Rocks May Think Interne Passing Juice
Leaving 1X Interne Passing Juice
Ultra Instinct Interne Passing Juice
Motor Physics Interne Passing Juice
Questions about ARC Prize Interne Passing Juice
All Roads Lead to Robotics Interne Passing Juice
Takeaways from DeepMind's RoboCat Paper Interne Passing Juice
Can LLMs Critique and Iterate on Their Own Outputs? Interne Passing Juice
How Can We Make Robotics More like Generative Modeling? Interne Passing Juice
All Roads Lead to Rome: The Machine Learning Job Market in 2022 Interne Passing Juice
Haikus about Effective Altruism Interne Passing Juice
Ranking YC Companies with a Neural Net Interne Passing Juice
Leaving Google Brain ✌️ Interne Passing Juice
To Understand Language is to Understand Generalization Interne Passing Juice
Just Ask for Generalization Interne Passing Juice
Robots Must Be Ephemeralized Interne Passing Juice
ML Mentorship: Some Q/A about RL Interne Passing Juice
Stonks are What You Can Get Away With Interne Passing Juice
Sovereign Arcade: Currency as High-Margin Infrastructure Interne Passing Juice
Science and Engineering for Learned Robots Interne Passing Juice
Don't Mess with Backprop: Doubts about Biologically Plausible Deep Learning Interne Passing Juice
How to Understand ML Papers Quickly Interne Passing Juice
Software and Hardware for General Robots Interne Passing Juice
My Criteria for Reviewing Papers Interne Passing Juice
Chaos and Randomness Interne Passing Juice
Free Office Hours for Non-Traditional ML Researchers Interne Passing Juice
Three Questions that Keep Me Up at Night Interne Passing Juice
Selected Quotes from "The Dark Ages of AI Panel Discussion" (1984) Interne Passing Juice
Differentiable Path Tracing on the GPU/TPU Interne Passing Juice
Robinhood, Leverage, and Lemonade Interne Passing Juice
Tips for Training Likelihood Models Interne Passing Juice
Normalizing Flows in 100 Lines of JAX Interne Passing Juice
Lessons from AI Research Projects: The First 3 Years Interne Passing Juice
Fun with Snapchat's Gender Swapping Filter Interne Passing Juice
What I Cannot Control, I Do not Understand Interne Passing Juice
Meta-Learning in 50 Lines of JAX Interne Passing Juice
Thoughts on the BagNet Paper Interne Passing Juice
Uncertainty: A Tutorial Interne Passing Juice
Dijkstra's, in Disguise Interne Passing Juice
Bots and Thoughts from ICRA2018 Interne Passing Juice
Aesthetically Pleasing Learning Rates Interne Passing Juice
Teacup: A Short Story Interne Passing Juice
Doing a Concurrent Masters at Brown Interne Passing Juice
Normalizing Flows Tutorial, Part 2: Modern Normalizing Flows Interne Passing Juice
Normalizing Flows Tutorial, Part 1: Distributions and Determinants Interne Passing Juice
Gamma Correction Interne Passing Juice
Expressivity, Trainability, and Generalization in Machine Learning Interne Passing Juice
Strong AI Ideas in Crystal Nights (Greg Egan, 2009) Interne Passing Juice
Summary of NIPS 2016 Interne Passing Juice
Tutorial: Categorical Variational Autoencoders using Gumbel-Softmax Interne Passing Juice
How Can a Deep Neural Network with ReLU Activations Approximate any Function? Interne Passing Juice
Riemann Summation and Physics Simulation are Statistically Biased Interne Passing Juice
Monte Carlo Variance Reduction Techniques in Julia Interne Passing Juice
A Beginner's Guide to Variational Methods: Mean-Field Approximation Interne Passing Juice
Adversarial Exploration Policies for Robust Model Learning Interne Passing Juice
Understanding and Implementing Deepmind's DRAW Model Interne Passing Juice
Generative Adversarial Nets in TensorFlow: Part I Interne Passing Juice
My Internship Experiences at Pixar, Google, and Two Sigma Interne Passing Juice
Reverse-Engineering Apps: a Step-by-Step Beginner's Guide Interne Passing Juice

Mots-clefs

Nuage de mots-clefs

jang feb eric sep jul jan subscribe learning nov apr

Cohérence des mots-clefs

Mot-clef Contenu Titre Mots-clefs Description Niveaux de titre
jul 5
jan 4
subscribe 4
learning 4
eric 3

Ergonomie

Url

Domaine : evjang.com

Longueur : 10

Favicon

Génial, votre site web dispose d'un favicon.

Imprimabilité

Aucun style CSS pour optimiser l'impression n'a pu être trouvé.

Langue

Bien. Votre langue est : en.

Dublin Core

Cette page ne profite pas des métadonnées Dublin Core.

Document

Doctype

HTML 5

Encodage

Parfait. Votre charset est UTF-8.

Validité W3C

Erreurs : 0

Avertissements : 0

E-mail confidentialité

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HTML obsolètes

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Astuces vitesse

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Parfait. Aucun style css inline n'a été trouvé dans vos tags HTML!
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Parfait, votre site web contient peu de fichiers javascript.
Parfait : votre site tire parti de gzip.

Mobile

Optimisation mobile

Icône Apple
Méta tags viewport
Contenu FLASH

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Robots.txt

https://evjang.com/robots.txt

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