Source of Arthur Samuel's definition of machine learning
Many people seem to agree that Arthur Samuel wrote or said in 1959 that machine learning is the "Field of study that gives computers the ability to learn without being explicitly programmed". For
machine learning - What is Ground Truth - Data Science Stack …
In machine learning, the term "ground truth" refers to the accuracy of the training set's classification for supervised learning techniques. This is used in statistical models to prove or …
Definition of a model in machine learning - Data Science Stack …
Jul 21, 2016 · In machine learning, the model is the center of gravity, everything revolves around it. Yet, people have different definitions of 'model'; but in my opinion, the best definition of …
What does Logits in machine learning mean?
Apr 30, 2018 · "One common mistake that I would make is adding a non-linearity to my logits output." What does the term "logit" means here or what does it represent ?
machine learning - What is the exact definition of VC dimension?
I'm studying machine learning from Andrew Ng Stanford lectures and just came across the theory of VC dimensions. According to the lectures and what I understood, the definition of VC …
neural network - What does embedding mean in machine …
Jun 18, 2019 · In the context of machine learning, an embedding is a low-dimensional, learned continuous vector representation of discrete variables into which you can translate high …
What does "baseline" mean in the context of machine learning?
Mar 2, 2019 · 28 What does "baseline" mean in the context of machine learning and data science? Someone wrote me: Hint: An appropriate baseline will give an RMSE of …
What does it mean when we say an algorithm/metric is agnostic
Oct 9, 2019 · 5 Problem I have all kinds of machine learning terms that co-occur with the word "agnostic", including model-agnostic learning, model-agnostic metric. From the dictionary, it …
machine learning - What's The Difference Between The Terms …
Predictor Variable: One or more variables that are used to determine or predict the target variable. Whereas Wikipedia contains the following definition of the word 'feature': Feature is an …
What are bias and variance in machine learning?
Aug 12, 2020 · Ensembles of Machine Learning models can significantly reduce the variance in your predictions. The Bias-Variance tradeoff If your model is underfitting, you have a bias …