What is batch in machine learning?
Answer / Ram Narayan Prajapati
A batch is a collection of training examples that are processed together, instead of processing each example individually. Batches can be used to improve the efficiency and stability of the learning algorithm.
| Is This Answer Correct ? | 0 Yes | 0 No |
How is bayes' theorem useful in a machine learning context?
Why is python so popular in machine learning?
What are the different methods for Sequential Supervised Learning?
What cross-validation technique would you use on a time series dataset?
What do you mean by parametric models?
Why is harmonic mean used to calculate f1 score and not the arithmetic mean?
Can you explain the differences between supervised, unsupervised, and reinforcement learning?
What is an imbalanced dataset? Can you list some ways to deal with it?
How will you set the threshold for credit card fraud detection model?
Describe dimension reduction in machine learning.
What should I learn before machine learning?
What is the difference between inductive and deductive learning?
AI Algorithms (74)
AI Natural Language Processing (96)
AI Knowledge Representation Reasoning (12)
AI Robotics (183)
AI Computer Vision (13)
AI Neural Networks (66)
AI Fuzzy Logic (31)
AI Games (8)
AI Languages (141)
AI Tools (11)
AI Machine Learning (659)
Data Science (671)
Data Mining (120)
AI Deep Learning (111)
Generative AI (153)
AI Frameworks Libraries (197)
AI Ethics Safety (100)
AI Applications (427)
AI General (197)
AI AllOther (6)