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67 votes
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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 ...
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44 votes
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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 ...
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  • 1,953
33 votes

Why is Python such a popular language in the AI field?

Practically all of the most popular and widely used deep-learning frameworks are implemented in Python on the surface and C/C++ under the hood. I think the main reason is that Python is widely used ...
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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 ...
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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 ...
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  • 369
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 ...
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  • 3,677
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 ...
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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 ...
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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 ...
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  • 205
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-...
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  • 1,146
5 votes
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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 ...
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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 ...
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  • 5,062
5 votes
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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 ...
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5 votes
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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, ...
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  • 9,379
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, ...
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4 votes
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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 ...
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4 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 ...
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  • 409
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 ...
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  • 141
4 votes
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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 ...
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4 votes
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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 ...
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4 votes
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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 ...
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4 votes
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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} ...
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  • 2,226
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 ...
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  • 141
4 votes
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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 ...
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4 votes
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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 ...
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  • 9,379
3 votes

Why is Python such a popular language in the AI field?

That’s because python is a modern scripting object-oriented programming language that has stylish syntax. Contrary to structural programming languages like java and C++, its scripting nature enables ...
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  • 141
3 votes

Why is Python such a popular language in the AI field?

Python has rich library, it is also object oriented, easy to program. It can be also used as frontend language. That's why it is used in artificial intelligence. Rather than AI it is also used in ...
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3 votes

Is there more than one Q-matrix update formula?

No, your second statement does not correctly implement the Q-learning update rule, which the first statement correctly implements.
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3 votes
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Where can I find an implementation of the wake-sleep algorithm?

I found the following detailed and well documented Python notebook, which uses only NumPy.
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  • 156
3 votes

Monte-Carlo, every-visit gridworld, exploring starts, python code gets stuck in foreverloop in episode generation

Your implementation of Monte Carlo Exploring Starts algorithm appears to be working as designed. This is a problem that can occur with some deterministic policies in the gridworld environment. It is ...
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