#model
Explore Books, Authors and Common Highlights on Model
Showing 56 of 56 highlights
Collaborative modeling enhances our understanding of complex systems.
From The Model Thinker by Scott E. Page
Mental models are frameworks that simplify complex realities.
Mental models are frameworks for thinking.
Regularization techniques help prevent overfitting.
From The Hundred-Page Machine Learning Book by Andriy Burkov
We need to rethink our economic and social models to adapt to these changes.
Models help us navigate complex systems.
From The Model Thinker by Scott E. Page
A good model is one that generalizes well to unseen data.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Regularization techniques are essential to prevent overfitting and improve the model's performance on unseen data.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
I want to be a role model for young women.
From Becoming by Michelle Obama
Regularization is a technique used to prevent overfitting by adding a penalty on the size of coefficients.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Mental models are frameworks that help us understand the world.
From Super Thinking: The Big Book of Mental Models by Gabriel Weinberg and Lauren McCann
Good models capture the essence of reality.
From The Model Thinker by Scott E. Page
Overfitting occurs when a model learns the training data too well, including its noise.
From The Hundred-Page Machine Learning Book by Andriy Burkov
You don’t need to scale to succeed.
From Company of One by Paul Jarvis
Our brains are designed to create models of the world.
From A Thousand Brains by Jeff Hawkins
The more models you have, the better your understanding.
From Super Thinking: The Big Book of Mental Models by Gabriel Weinberg and Lauren McCann
These models can have profound effects on people's lives, often with little accountability.
Models are tools for thinking and decision-making.
From The Model Thinker by Scott E. Page
The process of modeling can reveal hidden patterns.
From The Model Thinker by Scott E. Page
Our mental models shape the way we interpret the world around us.
Models are essential tools for decision-making.
From The Model Thinker by Scott E. Page
We can be the leaders we wish we had.
From Wolfpack by Abby Wambach
It is essential to interrogate the data and the models that shape our decisions.
The key to deep learning is representation learning, where the model learns to represent the input data in a way that makes it easier to solve the task at hand.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Mental models help you navigate uncertainty and complexity.
From Super Thinking: The Big Book of Mental Models by Gabriel Weinberg and Lauren McCann
Every time we learn something new, we are building a model of the world.
From The Master Algorithm by Pedro Domingos
Data is not enough; we need a model that tells us how the world works.
From The Book of Why by Judea Pearl
Collaboration enhances the effectiveness of models.
From The Model Thinker by Scott E. Page
Hyperparameter tuning can significantly affect the performance of your model.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Business models will need to adapt to the capabilities of prediction machines.
From Prediction Machines by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
Deep learning models are often seen as black boxes because it can be difficult to interpret how they make decisions.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
A model is a simplified representation of the world.
From The Model Thinker by Scott E. Page
Wonder Woman was designed to be a role model for girls.
Understanding the limits of our models helps us improve them.
From The Model Thinker by Scott E. Page
The only way to understand the world is to build a model of it.
Each model offers a unique perspective on reality.
From The Model Thinker by Scott E. Page
Every thought and action is a reflection of the models we create.
From A Thousand Brains by Jeff Hawkins
Understanding the predictive capabilities of AI can unlock new business models.
From Power and Prediction by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
The more models we have, the better our insights.
From The Model Thinker by Scott E. Page
Start small, learn quickly, and iterate until you find a sustainable business model.
From The Lean Startup by Eric Ries
Evaluation metrics guide the selection of the best model.
From The Hundred-Page Machine Learning Book by Andriy Burkov
The most important part of building a machine learning model is to understand the problem you are trying to solve.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Overfitting occurs when a model learns the noise in the training data instead of the underlying distribution.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
The Turing machine is a model of computation.
From The Annotated Turing by Charles Petzold
Overfitting occurs when a model learns the noise in the training data.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Every causal model can be viewed as a set of questions waiting to be answered.
From The Book of Why by Judea Pearl
The best predictions come from combining different models.
From The Model Thinker by Scott E. Page
Paradigms are the universally recognized scientific achievements that for a time provide model problems and solutions to a community of practitioners.
From The Structure of Scientific Revolutions by Thomas S. Kuhn
Mathematical models can perpetuate inequality and harm the most vulnerable.
Overfitting occurs when a model learns the training data too well, including noise and outliers, leading to poor generalization.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Transfer learning allows a model trained on one task to be adapted to a different but related task.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Effective decision-making relies on the right combination of models.
From The Model Thinker by Scott E. Page
To innovate, you must first identify the existing mental models.
Feature selection is crucial in building effective machine learning models.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Mental models are frameworks for thinking about the world.
From Super Thinking: The Big Book of Mental Models by Gabriel Weinberg and Lauren McCann
Our models of the world should reflect causal relationships.
From The Book of Why by Judea Pearl