Tag Collection

#algorithms

Explore Books, Authors and Common Highlights on Algorithms

Showing 44 of 44 highlights

The Turing machine is a simple abstract device that can simulate any computer algorithm.
Deep learning is a subfield of machine learning that uses algorithms inspired by the structure and function of the brain.
We must hold organizations accountable for their use of algorithms.
Data is the new oil, and algorithms are the refineries.

From The Master Algorithm by Pedro Domingos

The algorithms that govern our lives are often opaque, and they create a feedback loop that reinforces inequality.
The real world is messy, and algorithms must navigate that mess.

From The Master Algorithm by Pedro Domingos

Knowing a variety of algorithms allows you to choose the best one for the task at hand.

From Grokking Algorithms by Aditya Bhargava

The future of deep learning will depend on the interplay between advancements in algorithms and hardware capabilities.
The essence of computer science is the study of algorithms.
The algorithms that govern our lives are opaque and unaccountable.
Algorithms are the recipes for computation.
The ultimate goal of machine learning is to find the master algorithm.

From The Master Algorithm by Pedro Domingos

Understanding algorithms is essential to understanding the nature of computation.
The algorithms we create will shape our lives in ways we can't yet imagine.

From The Big Nine by Amy Webb

Algorithms are the new electricity.

From The Master Algorithm by Pedro Domingos

Understanding the algorithms behind AI is crucial for harnessing its power.

From Genius Makers by Cade Metz

As algorithms improve, so too must our understanding of their implications.
We are just beginning to scratch the surface of what algorithms can do.

From The Master Algorithm by Pedro Domingos

The more we rely on algorithms, the more we need to question their influence.
The lack of transparency in algorithms allows bias to thrive.
Every time we use a computer, we’re using algorithms.

From The Master Algorithm by Pedro Domingos

Algorithms are not neutral; they carry the biases of their creators.

From Atlas of AI by Kate Crawford

The concept of 'algorithm' is central to computer science.
Efficiency in algorithms is not just about speed; it's also about resourcefulness.

From Grokking Algorithms by Aditya Bhargava

The lack of transparency in algorithms can lead to discrimination and injustice.
You should measure the time it takes to execute your algorithms.
Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns.
The future of AI is not just about algorithms; it's about how we apply them.
Good algorithms lead to better performance and faster results.

From Grokking Algorithms by Aditya Bhargava

The study of algorithms is both an art and a science.

From Grokking Algorithms by Aditya Bhargava

Algorithms can help us make better decisions by processing vast amounts of data.

From The Master Algorithm by Pedro Domingos

An algorithm must be seen to be believed.
We must take responsibility for the algorithms we create.

From The Big Nine by Amy Webb

Computers do not think; they merely execute algorithms.
The master algorithm is the one algorithm that can learn anything from data.

From The Master Algorithm by Pedro Domingos

Understanding algorithms is key to understanding our world.

From The Master Algorithm by Pedro Domingos

Algorithms are not neutral — they reflect the biases of their creators.
Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data.
Understanding algorithms is crucial for understanding the modern world.

From The Master Algorithm by Pedro Domingos

The brain's functioning cannot be reduced to mere algorithms.
The future of computing is not about faster hardware, but smarter algorithms.
Algorithms are like recipes; they provide a set of instructions to solve a problem.

From Grokking Algorithms by Aditya Bhargava

In the end, all algorithms are trying to solve the same problem.

From The Master Algorithm by Pedro Domingos