New answers tagged machine-learning
0
votes
In-batch negative training Improves the results
Yes the In-batch negative training Improves the results but no objectively, it is more helpful in reducing the confusion of semantics of various pattern which I guess tends to happen in deep-layers.
...
- 101
1
vote
using bitmaps for storing and analyzing numeric data (use case: flight sim game AI)
The image processing and related models like CNNs are using the fact that pixels close together in an image are more related and small translations in objects are not important so using images do not ...
- 11
0
votes
What is the difference between parametric and non-parametric models?
I provided some details but the most important excerpt is from Stuart Russell and Peter Norvig's AIMA book:
A learning model that summarizes data with a set of parameters of fixed size (independent of ...
- 101
1
vote
I'd like some suggestions on how to effectively master machine learning. I'm new to this and I'm kinda lost
I think it depends on what you want to do with your knowledge and what background you are coming from. Also are you having any specific problem in mind you want to solve? because that could give a ...
- 119
0
votes
What is the difference between features and inputs in machine learning?
An input involves everything as a data. For example in image classification, all images are input to model while features are the kind of specific properties of that input images based on model will ...
2
votes
How to approach a toy classification problem using a neural network?
Although you label it as a toy system, I see three possible ways to simplify it and get the classifier to start working.
Instead of starting with 50 inputs, start with only 2 inputs.
Instead of ...
0
votes
Why do we need to find derivative for activation function?
This question is a duplicate to this one: Why is the derivative of the activation functions in neural networks important? you should go check the answer. Very informative!
- 1
1
vote
How is ChatGPT trained?
Step 2 is (mainly) useful to tune the style, alignement and general feeling of the ChatGPT answers, not the specifics of what is answered.
The actual "knowledge" comes simply from ingesting ...
- 1,054
0
votes
Accepted
I am confused of derivation steps of MAP for linear regression
For step 1: you're on the right track, but the derivation is easier if we leave everything conditional on $X$
$$p(\beta| X,y) = \frac{p(y| X, \beta) p(\beta | X)}{p(y |X)}$$
Now, the two key steps. ...
- 46
0
votes
NEAT can't solve XOR completely
Very old thread, but i will try to answer anyway. The configuration seems fine.
Try to implement a simple NE (without augmenting topologies) and check if it works.
...
1
vote
Accepted
What's the difference between Reliability, Resiliency, and Robustness?
I found this guy's thesis to be very helpful in understanding it:
Robustness: The model can be trained even with noisy and corrupted data. Simply put, if we add small perturbations to the image, can ...
- 1,037
1
vote
Why do LLMs need massive distributed training across nodes -- if the models fit in one GPU while batch decreases the variance of gradients?
The large batch size is mostly to speed things up as you point out. You could in principle train these models with batch size 1 and just do gradient accumulation, but then training would take muuuuch ...
- 271
1
vote
Second Language for Machine Learning
I recommend that you learn SQL as your second language. Most data scientists need to pull data from SQL databases. That doesn't mean you won't have to deal with NoSQL databases, but SQL is more common....
- 1,698
2
votes
Why do LLMs need massive distributed training across nodes -- if the models fit in one GPU while batch decreases the variance of gradients?
I don’t think the problem lies in the gradient or related stuffs - the problem here is the hardware limitation of GPU VRAM.
Sure, CLIP can fit in a single GPU, but what GPU are we talking about? I ...
- 1,037
Top 50 recent answers are included