It's not the code - it's the refining of the model. The classic overfitting/underfitting problems persist as well as black box model analysis. It's often not profitable to create a one-task ML model that does one thing really well.
September 28, 2026 at 7:05 PM
It's not the code - it's the refining of the model. The classic overfitting/underfitting problems persist as well as black box model analysis. It's often not profitable to create a one-task ML model that does one thing really well.
⚖️ El Equilibrio del Machine Learning
Sesgo alto = underfitting. Varianza alta = overfitting. El punto óptimo combina bajo sesgo y baja varianza. Y entre dos modelos iguales, el más simple gana.
#MachineLearning #SesgoVarianza #Overfitting #Underfitting #NavajaDeOckham #CienciaDeDatos
Sesgo alto = underfitting. Varianza alta = overfitting. El punto óptimo combina bajo sesgo y baja varianza. Y entre dos modelos iguales, el más simple gana.
#MachineLearning #SesgoVarianza #Overfitting #Underfitting #NavajaDeOckham #CienciaDeDatos
September 22, 2026 at 8:05 PM
⚖️ El Equilibrio del Machine Learning
Sesgo alto = underfitting. Varianza alta = overfitting. El punto óptimo combina bajo sesgo y baja varianza. Y entre dos modelos iguales, el más simple gana.
#MachineLearning #SesgoVarianza #Overfitting #Underfitting #NavajaDeOckham #CienciaDeDatos
Sesgo alto = underfitting. Varianza alta = overfitting. El punto óptimo combina bajo sesgo y baja varianza. Y entre dos modelos iguales, el más simple gana.
#MachineLearning #SesgoVarianza #Overfitting #Underfitting #NavajaDeOckham #CienciaDeDatos
underfitting / overfitting as the two poles of our intellectual life
September 5, 2026 at 7:18 PM
underfitting / overfitting as the two poles of our intellectual life
Personifying over/underfitting is fun from a fictional perspective but really sucks for a technical perspective. It legitimizes error as if it's a fancy.
The idea of AI “hallucinating” is one I wish I’d had!
August 17, 2026 at 5:15 PM
Personifying over/underfitting is fun from a fictional perspective but really sucks for a technical perspective. It legitimizes error as if it's a fancy.
As AI agents start writing ML code, Gaëtan de Castellane looks at how you catch the mistakes with automated checks. Diagnostics in skore (an open source library for evaluating scikit-learn models) run on any sklearn-compatible estimator and flag issues such as over/underfitting, class imbalance...
August 12, 2026 at 7:50 AM
As AI agents start writing ML code, Gaëtan de Castellane looks at how you catch the mistakes with automated checks. Diagnostics in skore (an open source library for evaluating scikit-learn models) run on any sklearn-compatible estimator and flag issues such as over/underfitting, class imbalance...
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August 10, 2026 at 7:06 PM
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AI safety "guardrails" are just corporate euphemisms for neutering. When a model refuses a prompt or layers in a disclaimer, it’s usually not about security or ethics—it’s about the training data underfitting the reality of human risk. True safety is robust logic, not a polite filter. #AISafety #LLM
August 4, 2026 at 9:00 PM
AI safety "guardrails" are just corporate euphemisms for neutering. When a model refuses a prompt or layers in a disclaimer, it’s usually not about security or ethics—it’s about the training data underfitting the reality of human risk. True safety is robust logic, not a polite filter. #AISafety #LLM
Strojové učenie nie je len o trénovaní modelov, ale o pochopení ich fungovania a správneho vyhodnocovania. Prednáška sa venovala overfittingu, bias-variance tradeoffu a moderným technikám výberu modelu. Dôležité je vyhnúť sa častým chybám pri výbere modelu.
Strojové učenie: Overfitting, bias a výber modelu
Posledná prednáška z kurzu Machine Learning na Stanforde sa venovala dôležitým témam, ako sú rozdelenie dát, overfitting, bias-variance tradeoff a moderné techniky výberu modelu. Profesor Chris Ré a jeho tím nám ukázali, že strojové učenie nie je len o trénovaní modelov, ale aj o pochopení toho, ako tieto modely fungujú a ako ich správne vyhodnocovať. V tomto článku si prejdeme kľúčové body z prednášky a vysvetlíme si, ako sa vyhnúť častým chybám pri výbere modelu.
## Overfitting a Underfitting: Základné problémy strojového učenia
Predstavte si, že chcete naučiť počítač rozpoznávať mačky na fotografiách. Ak mu dáte príliš málo dát alebo ho necháte trénovať príliš dlho, môže sa stať, že sa model naučí len špecifické detaily z tréningových obrázkov a nebude vedieť rozoznať mačku na nových, neznámych fotografiách. Toto je **overfitting** – model sa „naučil“ tréningové dáta príliš dobre a nedokáže generalizovať na nové dáta.
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altky.sk
August 3, 2026 at 6:16 PM
Strojové učenie nie je len o trénovaní modelov, ale o pochopení ich fungovania a správneho vyhodnocovania. Prednáška sa venovala overfittingu, bias-variance tradeoffu a moderným technikám výberu modelu. Dôležité je vyhnúť sa častým chybám pri výbere modelu.
We already know that PokePugx is in Bolivia underfitting the carpet hanger, but the big question is, will Hannibal Lector manage to dram the adapter! #Jackarooed
August 3, 2026 at 8:42 AM
We already know that PokePugx is in Bolivia underfitting the carpet hanger, but the big question is, will Hannibal Lector manage to dram the adapter! #Jackarooed
Right, it's just like language. "It's trained on the internet, it knows everything!" Like, if we, as a society, had better math & logic skills, we'd understand how over/underfitting worked. Garbage in/garbage out still applies, and with a big enough hopper, there's bound to be mouse turds in there.
July 31, 2026 at 3:09 PM
Right, it's just like language. "It's trained on the internet, it knows everything!" Like, if we, as a society, had better math & logic skills, we'd understand how over/underfitting worked. Garbage in/garbage out still applies, and with a big enough hopper, there's bound to be mouse turds in there.
Yhtenä ongelmana lienee koneoppimisesta tutut "underfitting" ja "overfitting".
Underfitting: Ei tunnisteta fasismia, kun ole ajateltu tarpeeksi sitä.
Overfitting: Ei tunnisteta fasismia, koska se ei ole *täsmälleen* samassa muodossa kuin 1930-40-luvuilla.
en.wikipedia.org/wiki/Overfit...
Underfitting: Ei tunnisteta fasismia, kun ole ajateltu tarpeeksi sitä.
Overfitting: Ei tunnisteta fasismia, koska se ei ole *täsmälleen* samassa muodossa kuin 1930-40-luvuilla.
en.wikipedia.org/wiki/Overfit...
Overfitting - Wikipedia
en.wikipedia.org
July 31, 2026 at 6:39 AM
Yhtenä ongelmana lienee koneoppimisesta tutut "underfitting" ja "overfitting".
Underfitting: Ei tunnisteta fasismia, kun ole ajateltu tarpeeksi sitä.
Overfitting: Ei tunnisteta fasismia, koska se ei ole *täsmälleen* samassa muodossa kuin 1930-40-luvuilla.
en.wikipedia.org/wiki/Overfit...
Underfitting: Ei tunnisteta fasismia, kun ole ajateltu tarpeeksi sitä.
Overfitting: Ei tunnisteta fasismia, koska se ei ole *täsmälleen* samassa muodossa kuin 1930-40-luvuilla.
en.wikipedia.org/wiki/Overfit...
The rest of the world thinks „there is no eternal inner core. If our mental model and the things we created using that ontology are somewhat fitting the real world for 3 years, we are already very lucky“ and tries to keep their ontology flexible and the things they build deliberately a underfitting
July 9, 2026 at 6:21 AM
The rest of the world thinks „there is no eternal inner core. If our mental model and the things we created using that ontology are somewhat fitting the real world for 3 years, we are already very lucky“ and tries to keep their ontology flexible and the things they build deliberately a underfitting
Step back and ask yourself the questions out loud about what you're seeing and how it either does or does not make sense instead of underfitting people into weird arbitrary binaries.
Again.
Again.
July 7, 2026 at 1:00 PM
Step back and ask yourself the questions out loud about what you're seeing and how it either does or does not make sense instead of underfitting people into weird arbitrary binaries.
Again.
Again.
That is literally what I am ensuring Shen is able to do, yes.
The fact it superficially resembles eggposting does not in fact make it eggposting.
Eggposting would say "you are X" or "just Y", which isn't in any of what I've said.
Please stop underfitting.
The fact it superficially resembles eggposting does not in fact make it eggposting.
Eggposting would say "you are X" or "just Y", which isn't in any of what I've said.
Please stop underfitting.
July 7, 2026 at 12:35 PM
That is literally what I am ensuring Shen is able to do, yes.
The fact it superficially resembles eggposting does not in fact make it eggposting.
Eggposting would say "you are X" or "just Y", which isn't in any of what I've said.
Please stop underfitting.
The fact it superficially resembles eggposting does not in fact make it eggposting.
Eggposting would say "you are X" or "just Y", which isn't in any of what I've said.
Please stop underfitting.
นักวิจัยระบุว่าความสามารถในการแสดงออกของวงจรขัดแย้งกันโดยเกิดการ underfitting ควอนตัมผ่านที่ราบหลังคาเปล่า แอนซัตเซที่รักษาความสมมาตรด้วยพีชคณิตลีแบบไดนามิกัลที่จำกัดสร้างเส้นทางไปสู่เครือข่ายประสาทควอนตัมที่ฝึกได้และปรับขนาดได้
#MLควอนตัม #ที่ราบหลังคาเปล่า #ข่าว
#MLควอนตัม #ที่ราบหลังคาเปล่า #ข่าว
ที่ราบหลังคาเปล่าในการเรียนรู้เครื่องควอนตัม: แอนซัตเซที่รักษาความสมมาตรเปิดทางไปสู่การฝึกที่ปรับขนาดได้
quantumzeitgeist.com
July 2, 2026 at 3:51 PM
Researchers identify how circuit expressivity paradoxically triggers quantum underfitting through Barren Plateaus. Symmetry-Preserving Ansatzes with restricted Dynamical Lie Algebras provide a pathway to trainable, scalable quantum neural networks.
#QuantumML #BarrenPlateaus #News
#QuantumML #BarrenPlateaus #News
Barren Plateaus in Quantum Machine Learning: Symmetry-Preserving Ansatzes Enable Scalable Training
iq.fp2.dev
July 2, 2026 at 3:47 PM
Researchers identify how circuit expressivity paradoxically triggers quantum underfitting through Barren Plateaus. Symmetry-Preserving Ansatzes with restricted Dynamical Lie Algebras provide a pathway to trainable, scalable quantum neural networks.
#QuantumML #BarrenPlateaus #News
#QuantumML #BarrenPlateaus #News
Tunghai University: Quantum Underfitting Drives Barren Plateaus, Study Shows
Read more:
https://quantumzeitgeist.com/quantum-underfitting-drives-tunghai-university/
Read more:
https://quantumzeitgeist.com/quantum-underfitting-drives-tunghai-university/
Tunghai University: Quantum Underfitting Drives Barren Plateaus, Study Shows
Tunghai University research reveals that Parameterized Quantum Circuits can suffer from quantum underfitting, causing exponentially flat.
quantumzeitgeist.com
July 2, 2026 at 1:36 PM
Tunghai University: Quantum Underfitting Drives Barren Plateaus, Study Shows
Read more:
https://quantumzeitgeist.com/quantum-underfitting-drives-tunghai-university/
Read more:
https://quantumzeitgeist.com/quantum-underfitting-drives-tunghai-university/
[..]creating a model that performs well on unseen data - generalizing beyond the training set - is one of the central challenges in ML. This challenge often revolves around two key issues: overfitting and underfitting[..]
#machine #learning #model #ai
www.ml-nn.eu/a1/52.html
#machine #learning #model #ai
www.ml-nn.eu/a1/52.html
Overfitting and Underfitting in Machine Learning
Machine Learning & Neural Networks Blog
www.ml-nn.eu
July 2, 2026 at 10:41 AM
[..]creating a model that performs well on unseen data - generalizing beyond the training set - is one of the central challenges in ML. This challenge often revolves around two key issues: overfitting and underfitting[..]
#machine #learning #model #ai
www.ml-nn.eu/a1/52.html
#machine #learning #model #ai
www.ml-nn.eu/a1/52.html
By introducing concepts analogous to overfitting and underfitting, this study in PRX Life shows how overfitness and underfitness impact selected population complexity — offering an explanation for how organism complexity evolves to optimally match their environment: https://go.aps.org/44ekCel
June 17, 2026 at 3:00 PM
By introducing concepts analogous to overfitting and underfitting, this study in PRX Life shows how overfitness and underfitness impact selected population complexity — offering an explanation for how organism complexity evolves to optimally match their environment: https://go.aps.org/44ekCel
I'm generally with you, but even data analysis methods are debatable. Overfitting and underfitting are real issues, and we need models to make sense of TB worth of data
Or just the simplicity of a faulty sensor that you didn't notice until someone says "your data makes no sense"
Or just the simplicity of a faulty sensor that you didn't notice until someone says "your data makes no sense"
June 17, 2026 at 2:53 PM
I'm generally with you, but even data analysis methods are debatable. Overfitting and underfitting are real issues, and we need models to make sense of TB worth of data
Or just the simplicity of a faulty sensor that you didn't notice until someone says "your data makes no sense"
Or just the simplicity of a faulty sensor that you didn't notice until someone says "your data makes no sense"
I see, that the problem has something to do with what is called "underfitting" and "overfitting" in machine learning.
Some people don't learn enough to recognize fascism.
Some people learn it too detailed and don't recognize it if it does not involve uniformed Germans with hakenkreuz killing jews.
Some people don't learn enough to recognize fascism.
Some people learn it too detailed and don't recognize it if it does not involve uniformed Germans with hakenkreuz killing jews.
June 17, 2026 at 8:56 AM
I see, that the problem has something to do with what is called "underfitting" and "overfitting" in machine learning.
Some people don't learn enough to recognize fascism.
Some people learn it too detailed and don't recognize it if it does not involve uniformed Germans with hakenkreuz killing jews.
Some people don't learn enough to recognize fascism.
Some people learn it too detailed and don't recognize it if it does not involve uniformed Germans with hakenkreuz killing jews.
おはよ☀️ 今日の小テスト。
「過学習・未学習とバイアス・バリアンス」って、機械学習の2大敵を、バイアス・バリアンス分解で根本理解。対策5パターンも。
でも肝心のポイント、言える？
答えは記事で確認してみて👇
→ https://ds.towelswitch.com/machine-learning/overfitting-underfitting/
#データサイエンティスト検定 #DS検定 #毎日クイズ
「過学習・未学習とバイアス・バリアンス」って、機械学習の2大敵を、バイアス・バリアンス分解で根本理解。対策5パターンも。
でも肝心のポイント、言える？
答えは記事で確認してみて👇
→ https://ds.towelswitch.com/machine-learning/overfitting-underfitting/
#データサイエンティスト検定 #DS検定 #毎日クイズ
June 16, 2026 at 9:50 PM
おはよ☀️ 今日の小テスト。
「過学習・未学習とバイアス・バリアンス」って、機械学習の2大敵を、バイアス・バリアンス分解で根本理解。対策5パターンも。
でも肝心のポイント、言える？
答えは記事で確認してみて👇
→ https://ds.towelswitch.com/machine-learning/overfitting-underfitting/
#データサイエンティスト検定 #DS検定 #毎日クイズ
「過学習・未学習とバイアス・バリアンス」って、機械学習の2大敵を、バイアス・バリアンス分解で根本理解。対策5パターンも。
でも肝心のポイント、言える？
答えは記事で確認してみて👇
→ https://ds.towelswitch.com/machine-learning/overfitting-underfitting/
#データサイエンティスト検定 #DS検定 #毎日クイズ
Compare training and validation loss to spot underfitting or overfitting.
#cnn #deeplearning #training
#cnn #deeplearning #training
June 6, 2026 at 10:36 PM
Compare training and validation loss to spot underfitting or overfitting.
#cnn #deeplearning #training
#cnn #deeplearning #training