86 votes
Accepted

What is self-supervised learning in machine learning?

Introduction The term self-supervised learning (SSL) has been used (sometimes differently) in different contexts and fields, such as representation learning [1], neural networks, robotics [2], natural ...
user avatar
  • 33.8k
67 votes
Accepted

Is a switch from R to Python worth it?

I want to reframe your question. Don't think about switching, think about adding. In data science you'll be able to go very far with either python or r but you'll go farthest with both. Python and ...
user avatar
  • 880
61 votes

What is the difference between artificial intelligence and machine learning?

Machine learning has been defined by many people in multiple (often similar) ways [1, 2]. One definition says that machine learning (ML) is the field of study that gives computers the ability to learn ...
user avatar
  • 820
43 votes
Accepted

What is the relation between Q-learning and policy gradients methods?

However, both approaches appear identical to me i.e. predicting the maximum reward for an action (Q-learning) is equivalent to predicting the probability of taking the action directly (PG). Both ...
user avatar
  • 23.9k
40 votes

What is the difference between a convolutional neural network and a regular neural network?

TLDR: The convolutional-neural-network is a subclass of neural-networks which have at least one convolution layer. They are great for capturing local information (e.g. neighbor pixels in an image or ...
user avatar
39 votes

What's the difference between model-free and model-based reinforcement learning?

What's the difference between model-free and model-based reinforcement learning? In Reinforcement Learning, the terms "model-based" and "model-free" do not refer to the use of a ...
user avatar
  • 23.9k
36 votes
Accepted

What is the difference between strong-AI and weak-AI?

The terms strong and weak don't actually refer to processing, or optimization power, or any interpretation leading to "strong AI" being stronger than "weak AI". It holds conveniently in practice, but ...
user avatar
  • 536
32 votes
Accepted

How is a deep neural network different from other neural networks?

The difference is mostly in the number of layers. For a long time, it was believed that "1-2 hidden layers are enough for most tasks" and it was impractical to use more than that, because training ...
user avatar
32 votes

Is a switch from R to Python worth it?

Of course, this type of questions will also lead to primarily opinion-based answers. Nonetheless, it is possible to enumerate the strengths and weakness of each language, with respect to machine ...
user avatar
  • 33.8k
31 votes

Why does C++ seem less widely used than Python in AI?

You don't need a powerful language for programming AI. Most of the developers are using libraries like Keras, Torch, Caffe, Watson, TensorFlow, etc. Those low level libraries are highly optimized and ...
user avatar
  • 369
29 votes

What's the difference between model-free and model-based reinforcement learning?

Model-based reinforcement learning has an agent try to understand the world and create a model to represent it. Here the model is trying to capture 2 functions, the transition function from states $T$ ...
user avatar
24 votes

What is the difference between artificial intelligence and machine learning?

Machine learning is a subset of artificial intelligence. Roughly speaking, it corresponds to its learning side. There is no "official" definitions, boundaries are a bit fuzzy.
user avatar
22 votes

Are humans superior to machines in chess?

Losing games to computers because of mistakes made under time pressure was probably a thing about 20 years ago, when Kasparov lost to DeepBlue after such a mistake(correction: it was Kramnik with the ...
user avatar
  • 870
21 votes

What's the difference between model-free and model-based reinforcement learning?

In reinforcement learning (RL), there is an agent which interacts with an environment (in time steps). At each time step, the agent decides and executes an action, $a$, on an environment, and the ...
user avatar
  • 33.8k
21 votes
Accepted

What is the difference between First-Visit Monte-Carlo and Every-Visit Monte-Carlo Policy Evaluation?

The first-visit and the every-visit Monte-Carlo (MC) algorithms are both used to solve the prediction problem (or, also called, "evaluation problem"), that is, the problem of estimating the value ...
user avatar
  • 33.8k
19 votes
Accepted

What does AI software look like, and how is it different from other software?

Code in AI is not in principle different from any other computer code. After all, you encode algorithms in a way that computers can process them. Having said that, there are a few points where your ...
user avatar
  • 5,062
19 votes

What are the main differences between skip-gram and continuous bag of words?

So as you're probably already aware of, CBOW and Skip-gram are just mirrored versions of each other. CBOW is trained to predict a single word from a fixed window size of context words, whereas Skip-...
user avatar
18 votes
Accepted

What is the difference between machine learning and deep learning?

Deep learning is a specific variety of a specific type of machine learning. So it's possible to learn about deep learning without learning all of machine learning, but it requires learning some ...
user avatar
18 votes

What is the difference between tree search and graph search?

There is always a lot of confusion about this concept, because the naming is misleading, given that both tree and graph searches produce a tree (from which you can derive a path) while exploring the ...
17 votes

What is the difference between a convolutional neural network and a regular neural network?

Convolutional Neural Networks (CNNs) are neural networks with architectural constraints to reduce computational complexity and ensure translational invariance (the network interprets input patterns ...
user avatar
17 votes
Accepted

What is the difference between actor-critic and advantage actor-critic?

Actor-Critic is not just a single algorithm, it should be viewed as a "family" of related techniques. They're all techniques based on the policy gradient theorem, which train some form of critic that ...
user avatar
  • 9,379
17 votes
Accepted

How does LSTM in deep reinforcement learning differ from experience replay?

How does this method differ from the experience replay, as they both use past information in the training? What's the typical application of both techniques? Using a recurrent neural network is one ...
user avatar
  • 23.9k
17 votes

What is self-supervised learning in machine learning?

Self-supervised learning is when you use some parts of the samples as labels for a task that requires a good degree of comprehension to be solved. I'll emphasize these two key points, before giving an ...
user avatar
  • 481
16 votes

What is the difference between artificial intelligence and machine learning?

Artificial intelligence According to the book Artificial Intelligence: A Modern Approach (section 1.1), artificial intelligence (AI) has been defined in multiple ways, which can be organized into 4 ...
16 votes

Why is Sanskrit the best language for AI?

Rick Briggs refers to the difficulty an artificial intelligence would have in detecting the true meaning of words spoken or written in one of our natural languages. Take for example an artificial ...
user avatar
16 votes
Accepted

What are the differences between Q-Learning and A*?

Q-learning and A* can both be viewed as search algorithms, but, apart from that, they are not very similar. Q-learning is a reinforcement learning algorithm, i.e. an algorithm that attempts to find a ...
user avatar
  • 33.8k
15 votes
Accepted

Why has the cross-entropy become the classification standard loss function and not Kullback-Leibler divergence?

When it comes to a classification problem in machine learning, the cross-entropy and the KL divergence are equal. As already stated in the question, the general formula is this: $$H(p, q) = H(p) + D_{...
user avatar
  • 1,877
15 votes
Accepted

How is BERT different from the original transformer architecture?

What is a transformer? The original transformer, proposed in the paper Attention is all you need (2017), is an encoder-decoder-based neural network that is mainly characterized by the use of the so-...
user avatar
  • 33.8k
14 votes
Accepted

When is deep learning overkill?

It's all about Return On Investment. If DL is "worth doing", it's not overkill. If the cost of using DL (computer cycles, storage, training time) is acceptable, and the data available to train it is ...
user avatar
  • 671
14 votes

Why does C++ seem less widely used than Python in AI?

C++ is actually one of the most popular languages used in the AI/ML space. Python may be more popular in general, but as others have noted, it's actually quite common to have hybrid systems where the ...
user avatar
  • 3,677

Only top scored, non community-wiki answers of a minimum length are eligible