machine learning - What is the difference between AI, ML, NN and …
Nov 18, 2020 · Machine Learning (ML) Neural Network (NN) Deep Learning (DL) Data Science My current understanding is that each of these encapsulates some set of algorithms. I feel like, …
Source of Arthur Samuel's definition of machine learning
14 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 …
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 …
machine learning - How to train ML model with multiple variables ...
Oct 2, 2018 · I am trying to learn Machine Learning concepts these days. I understand in a traditional ML data, we will have features and labels. I have following toy data in my mind …
machine learning - How to determine which features matter the …
Mar 12, 2020 · I also have a column that shows which loan has been selected at the end by the user per each search. I am looking to find out which features of the loan were most important …
machine learning - Do model training pipeline should run on dev ...
Feb 21, 2023 · Do we train the model in three different environments? (IMO, No, but looking for justifications and understanding industry best practices) How do the dev, staging, and …
machine learning - What's The Difference Between The Terms …
The difference is likely in the community that uses the terms. For computer vision/ml, the term "feature" is commonly used.
Best practices to store Python machine learning models
What are the best practices to save, store, and share machine learning models? In Python, we generally store the binary representation of the model, using pickle or joblib.
Training set and test set size - Data Science Stack Exchange
Jan 19, 2022 · In the machine learning world, data scientists are often told to train a supervised model on a large training dataset and test it on a smaller amount of data. The reason why …
machine learning - What are the disadvantages of Azure's ML vs a …
Azure ML seems to allow hooks into Python or R to give you more control and it sure would be appealing to have to do less work to get the same results. What are the known disadvantages …