The elements of Reinforcement Learning
Machine learning and Artificial Intelligence are becoming hot technologies right now. While most of the available technologies and…
Machine learning and Artificial Intelligence are becoming hot technologies right now. While most of the available technologies and…
What is a Data Mart a Data mart is defined as a subset of data form a data…
In his 2017 book “From bacteria to Bach and back” Daniel Dennett claims that consciousness is not a…
Machine translation (MT), is the process of translating text from one source language into another target language, is…
Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured documents. In most of the cases…
Convolutional Neural Network (CNNs), are mainly known for Computer Vision tasks. They, nevertheless, have various applications in text…
Mohamed Ben Haddou
Co-founder and Chief Executive Officer of Mentis. He brings more than 15 years of experience in R&D and Business Development. After spending more than 6 years of Research in Artificial Intelligence inside IRIDIA ( Artificial Intelligence laboratory of ULB) he joined the company Mars. He participated in developing efficient ways of analyzing large databases of media-data. in 2005 He then founded Mentis. He holds a Master Degree in Theoretical Physics and PhD in Artificial Intelligence (AI) from the Université Libre de Bruxelles (ULB).
Machine learning and Artificial Intelligence are becoming hot technologies right now. While most of the available technologies and expertise is centered around supervised and unsupervised techniques, the real AI paradigm as nature present it to us lies int the ability to learn while interacting with the environment. Traditional supervised learning is unrealistic, as no real…
What is a Data Mart a Data mart is defined as a subset of data form a data warehouse (but not only) of an organization that is limited to a specific business unit or group of users. It is a subject-oriented database and is also known as High-Performance Query Structures (HPQS). If implemented correctly,…
In his 2017 book “From bacteria to Bach and back” Daniel Dennett claims that consciousness is not a mysterious entity and is the result of a Darwinian evolution followed by a post Darwinian intelligent design. He presents us with hypothetical creatures resulting from a Darwin process. Each of them uses a Darwinian process on increasingly…
Machine translation (MT), is the process of translating text from one source language into another target language, is one of the most important applications of NLP. MT is a sequence-to-sequence task. There are a lot of them in NLP. We have a sequence of words in one language as an input, and we want to…
Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured documents. In most of the cases this activity concerns processing human language texts by means of natural language processing (NLP). IE is a general category which has various sub-categories, such as entity extraction, event extraction, relation extraction, coreference resolution, and entity linking to name a…
Convolutional Neural Network (CNNs), are mainly known for Computer Vision tasks. They, nevertheless, have various applications in text mining. In this post I will provide insights into some of the most popular NLP applications. We have seen that CNN can capture local features and combinations of these features. This makes them primarily suitable for document…
Why NLP is difficult? Text classification is complex, much more complex than image classification for example. The reason, is that nearly all what you need to classify an image is in the image itself. there is no need for an external supposed knowledge. While in text this is not the case. Generally language always refers…
In this series of blog posts, I’ll be exploring the Intelligent Virtual Assistant (IVA) trends and analyzing it from the technological point of view. I‘ll be thinking about what needs to be done and how to achieve this next level of IVAs. To understand what I mean by next level IVA, I will first define…
In a previous article I introduced Convolutional Neural Networks (CNN) in an intuitive way. In this article I will present few of the modern architectures of the CNN. Convolutional networks have been showing exceptional results in image classification more than a decade ago. Here we will review some of standard CNN architectures and the context…
Introduction Convolutional neural networks (also called CNNs or ConvNets) are neural networks used traditionally to classify images, for example to identify faces, objects, street signs, tumors,… They have the ability to recognise any kind of data if they get trained with a suitable dataset. CNNs are not limited to image recognition, they have been applied…
In the last post I introduced Word2vec and presented it using intuitive concepts. in this post I will implement these ideas in python. I will be using the Open American National Corpus (http://www.anc.org/), which consists of roughly 15 million spoken and written words from a variety of sources. Specifically, we will be using the sub…
In this post I will be implementing the Word2vec algorithm with negative sampling from scratch using python. Implementing this from scratch allow to have a better grasp the inner operations of word2vec’s skip-gram and negative sampling approach. For our analysis, we will use the Open American National Corpus (http://www.anc.org/), which consists of roughly 15 million…
Introduction The goal of any classification algorithm is to predict a value c given the value of a vector x of input features. In classification problems, c is a discrete class label, whereas in a regression problem it is a continuous variable. From a probabilistic point of view, the goal is to find the conditional…
In this article I’m going to analyze a marketing database using Principal Component Analysis or PCA. PCA is particularly useful when we are working with data sets that have a lot of variables. These datasets cannot be easily visualized the in its raw format, and hence it is difficult to get a sense of the…
Markov chains is one of the oldest ways to generate quite believable text. Rather than generating text by randomly selecting characters (possible but completely impractical), we use the Markov property that follows the chain of linked events, where what get generated next depends only on what is generated currently. Typically generating text trough, a Markov process…
What is Context free grammar? A Context-Free Grammar (CFG) is a set of rules that define what is and is not a valid sequence of “words” of a language. The rules aren’t limited to the production of text and can be applied in all fields where a fixed number of rules structures the production of…
Text generation is a hot topic right now in the domain of Artificial intelligence. Any advanced artificial intelligence will have the ability to interact with us, humans. And this means the ability to talk our language to understand us and to communicate back to us. Ultimately the IA needs to truly interact with us in…
Now I will start designing the engine of the virtual assistant. This engine will be the central nervous system of ow tool. The first approach that I will follow here is very simple. This approach is summarised in the following diagram. In this design the text to speech convert speech to text. This…
In this post We will be going to set up the system for voice recognition and voice generation. Before delving into the details, lets structure our work space. Lets create a folder structure that will hold our project, but first we need to give a name to our assistant. In my case I will call…
When users interact with internet content it is important, specifically for recommendation systems, to get their feedback. There are mainly 3 ways that are commonly used to gather users feedback on the Internet. In the our case the content scored by the users could be any web entity such as news articles, products, vendors,… 1-…
In this part we will be setting up the development for python. I’ll be setting up the environment for a Mac os-x. The given instructions can also be applied to Linux systems. Later as I will test in a window environment I will update the article and add windows specific instructions. I suppose that python…
“We all need a personal assistant, and we’ll all have one” In this series of blog posts, I’ll walk you through building and designing a basic virtual assistant like Apple’s Seri. Before delving into the details of how to build such an assistant, lets first explore what virtual assistants are and what are the players…
Alan Turing, the English computer scientist and mathematician proposed an experiment that becomes known by his name (the Turing test). In this test, a computer could be said “intelligent” if a human interrogator could not tell it apart, through conversation, from a human being. Is this Test still valid today? Is a machine that…