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 ...
48
votes
Accepted
Why is Python such a popular language in the AI field?
Python comes with a huge amount of inbuilt libraries. Many of the libraries are for Artificial Intelligence and Machine Learning. Some of the libraries are TensorFlow (which is a high-level neural ...
35
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 ...
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 ...
16
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 ...
9
votes
Why is Python such a popular language in the AI field?
What attracts me to Python for my analysis work is the "full-stack" of tools that are available by virtue of being designed as a general purpose language vs. R as a domain specific language. The ...
8
votes
Why is Python such a popular language in the AI field?
Python has a standard library in development, and a few for AI. It has an intuitive syntax, basic control flow, and data structures. It also supports interpretive run-time, without standard compiler ...
7
votes
Accepted
In Q-learning, shouldn't the learning rate change dynamically during the learning phase?
Yes you can decay the learning rate in Q-learning, and yes this should result in more accurate Q-values in the long term for many environments.
However, this is something that is harder to manage ...
6
votes
Accepted
Can genetic algorithms be used to learn to play multiple games of the same type?
Genetic algorithms and Neural Networks both are "general" methods, in the sense that they are not "domain-specific", they do not rely specifically on any domain knowledge of the game of Mario. So yes, ...
6
votes
Is a switch from R to Python worth it?
I didn't have this choice because I was forced to move from R to Python:
It depends on your environment: When you are embedded in an engineer department, working technical group or something similar ...
5
votes
Why does C++ seem less widely used than Python in AI?
It depends how flexible it needs to be: if you have a fully-fledged system ready for production, which is not going to need much adjusting, then C++ (or even C) might be fine. You need to put a lot of ...
5
votes
Accepted
How to refine K-means clustering on a data set?
The usual parameters to adjust in a k-means:
Number of clusters (recall many clusters can have same label).
Distance definition (euclidean is the most basic, Gauss is an
improvement)
Selection of ...
5
votes
How do I compute the structural similarity between sentences?
The best approach at this time (2019):
The most efficient approach now is to use Universal Sentence Encoder by Google (paper_2018) which computes semantic similarity between sentences using the dot ...
5
votes
How do I compute the structural similarity between sentences?
Firstly, before we commence I recommend that you refer to similar questions on the network such as https://datascience.stackexchange.com/questions/25053/best-practical-algorithm-for-sentence-...
5
votes
Accepted
What is the typical AI approach for solving blackjack?
Blackjack is usually modelled using Monte Carlo (MC) Methods. There is a lot of literature on MC methods which is interesting on its own right but here is a paper describing how MC is applied to ...
5
votes
Does it make sense to apply softmax on top of relu?
Does it make sense?
In general, yes it is interpretable, back propagation will work, and the NN can be optimised.
By using ReLU, the default network has a minimum logit of $0$ for the softmax input, ...
5
votes
Accepted
Why isn't my decision tree classifier able to solve the XOR problem properly?
I can reproduce this problem for an even more easily separable dataset:
The ideal tree for it should be as follows:
However, when I run DecisionTreeClassifier ...
5
votes
Accepted
q learning appears to converge but does not always win against random tic tac toe player
The primary issue I see is that in the loop through time steps t in every training episode, you select actions for both players (who should have opposing goals to ...
5
votes
Creating a support chat bot for my business
First and foremost, do not use GPT/OpenAI for customer-facing applications. You end up with a mess. GPT is great for creative work, but not for production. GPT is a probabilistic language model, and ...
4
votes
Why is Python such a popular language in the AI field?
It's a mix of many factors that together make it a very good option to develop cognitive systems.
Quick development
Rapid prototyping
Friendly syntax with almost human-level readability
Diverse ...
4
votes
Accepted
What do the values of the leaves of the decision tree represent?
Decision tree nodes are split bases on the number of data samples, these numbers indicate the number of data samples they are fit to.
In your case samples = 256. It is further split into two nodes of ...
4
votes
Accepted
How can I develop an object detection system that counts the number of objects and determines their position in an image?
If you want to get experience, you should probably start with some easier task. Object detection and localization are relatively hard and writing a neural network and image processing pipeline from ...
4
votes
Accepted
Creating a self learning Mario Kart game AI?
What aspects of AI would be most applicable to creating a self learning game AI for a racing game (Q-Learning, NEAT etc)
In general, you are looking at a problem that involves sequential decision ...
4
votes
Accepted
Why am I getting the incorrect value of lambda?
$TD(\lambda)$ return has the following form:
\begin{equation}
G_t^\lambda = (1 - \lambda) \sum_{n=1}^{\infty} \lambda^{n-1} G_{t:t+n}
\end{equation}
For you MDP $TD(1)$ looks like this:
\begin{align}
...
4
votes
Is a switch from R to Python worth it?
I would say yes. Python is better than R for most tasks, but R has its niche and you would still want to use it in many circumstances.
Additionally, learning a second language will improve your ...
4
votes
Is there an open-source implementation for graph convolution networks for weighted graphs?
You can use Pytorch_Geometric library for your projects. Its supports weighted GCNs. It is a rapidly evolving open-source library with easy to use syntax. It is mentioned in the landing page of ...
4
votes
Accepted
How to make spacy lemmatization process fast?
https://spacy.io/api/lemmatizer just uses lookup tables and the only upstream task it relies on is POS tagging, so it should be relatively fast. For large amounts of text, SpaCy recommends using ...
4
votes
Accepted
Can TensorFlow, PyTorch, and other mainstream ML frameworks be used for research-grade work in AI?
Your statement that researchers build their network from the ground-up using C++ or some other low level library couldn't be further from the truth.
You could take a look at this analysis showing the ...
4
votes
Does the order of a Numpy array matter for CNN classification?
It shouldn't matter for the accuracy of the network. But note that tensorflow/keras uses the (N, W, H, C) convention whereas pytorch uses the (N, C, W, H). So depending on what library you use, you ...
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