MMORPG’s business model Nowadays, MMORPGs are so popular that their market is worth over a billion dollars in 2019 and it is expected to keep growing during the following years. They can count over 10 million active monthly players, and, as expected, their huge base of players is one the keys to their success. In fact, these kinds of games belong to the (FTP) Free-To-Play … Continue reading Predicting players’ departure in MMORPGs
Have you ever heard the word “MMORPG“? Probably yes, but you don’t know its meaning, isn’t it? Well, then I’m going to tell you, it means Massive Multiplayer Online Role Play Games. They are that kind of videogames where each user controls a digital avatar and interacts with other online users in a digital world. You probably have already heard of many of them such … Continue reading Predicting players’ behaviors in MMORPGs
If we want machines to think, we need to teach them to see Fei-Fei Li Computer vision is one of the most challenging and fascinating field of machine learning. We can say it acquired popularity back in 2010 since the ILSVRC (Large Scale Visual Recognition Challenge) competition was introduced by Alex Berg from Stony Brook, Jia Deng from Princeton & Stanford, and Fei-Fei Li from … Continue reading CNN: Convolutional Neural Networks
In the last post we talked about Variational Auteoncoders (VAE), powerful generative machine learning model able to generate new data based on previously seen samples. In this post we are going to implement one and use it to generate handritten digits. Will you recognize which digits have been written by a human and which ones have been written by a machine? We are going to … Continue reading Generating handwritten digits with VAE and Zhusuan
Here are some digits, first of all, I ask you “Can you recognize them?” Maybe not all of them, some digits are actually blurred while others are quite ambiguous. Now let me show you another set of digits. It sounds like someone wrote many “6”s, all of the are very similar, but not the same. The second question I want to propose now is “Have … Continue reading VAE: Variational Autoencoder
We have already discussed whether machines can think in a previous post. Now, the next question I would like to propose is: “Can machines dream?”. After reading that, you may think that I got completely crazy, that I lost my head somewhere in the cosmos and came back with new extravagant ideas. Well…Actually, you are not so wrong. My head, while navigating among the deepest … Continue reading Deep Dreaming
Logistic regression is a supervised machine learning model used for classification tasks. It works by learning an hyperplane defined by some coefficients (or weights) θ = [θ0,…,θd] such that it can split the data into two subsets according to their labels. These coefficients θ are composed by a weights vector w = [w1,…,wd] plus a bias term b. For simplicity, we will consider a binary … Continue reading Logistic regression
PCA (Principal Component Analysis) is an unsupervised machine learning algorithm used to reduce the dimensionality of the given data. It has first been invented by Karl Pearson (1901) and independently developed by Harold Hotelling (1933). Dimensionality reduction refers to the mapping of the original high-dimensional data onto a lower-dimensional space, thus reducing the risk of model overfitting and improving the generalization ability of the model … Continue reading PCA: Principal Component Analysis
Anomaly detection plays an important role in the management of modern large-scale distributed systems. Logs are widely used for anomaly detection, recording system runtime information, and errors. Traditionally, operators have to go through the logs manually with keyword searching and rule matching. The increasing scale and complexity of modern systems, however, make the volume of logs explode, which renders the infeasibility of manual inspection. To … Continue reading Log analysis for anomaly detection
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