Posts Tagged ‘Machine Learning’

04
Oct
Deep Learning from the basis
  • Pablo Navarro
  • 348 Views
  • 0 Comment
  • Artificial Intelligence . Deep Learning . Inteligencia Artificial . Machine Learning . Neural Networks . Perceptrones . Redes Neuronales .

As mentioned in the previous article “Deep Learning, only for professional pilots”: there is no point in buying a Ferrari with a year´s license. However, we want to evoke in favor of Deep Learning and we thought it's important to start somewhere. We want to start with a purely informative article, for those to whom Deep Learning sounds like a science fiction or a horror movie. We do not pretend you end up using neural network models on a daily basis, we are just interested that you have the base to be able to make the leap into the world of Deep Learning. Starting from the basics, it is convenient to ask ourselves the question: What is Deep Learning? The…

29
Aug
Semi-Supervised Learning… the great unknown
  • Alfonso Ibañez
  • 3374 Views
  • 0 Comment
  • Algoritmos Semisupervisados . Big Data . Machine Learning .

In recent years much progress has been made in solving complex problems thanks to Artificial Intelligence algorithms. These algorithms need a large volume of information to discover and learn, continuously, hidden patterns in the data. However, this is not the way the human mind learns. A person does not require millions of data and multiple iterations to solve a particular problem, since all they need are some examples to solve it. In this context, techniques such as semi-supervised learning or semi-supervised learning are playing an important role nowadays. Within Machine Learning techniques, we can find several well-differentiated approaches (see Figure 1). The supervised algorithms deal with labeled data sets and their objective is to construct predictive models, either classification (estimating…

28
Jun
High impact technologies: artificial intelligence in our daily life
  • Carlos Lorenzo
  • 4156 Views
  • 0 Comment
  • Big Data . Inteligencia Artificial . Machine Learning . Synergic Partners .

Artificial intelligence is no longer science fiction, although it is far from the robots we see in Hollywood movies. Currently, large companies have joined the challenge of integrating, in one way or another, artificial intelligence within their own business models. The purposes are vary widely: from improving the customer experience; through bots Like Siri (Apple), Cortana (Windows), Alexa (Amazon) or Aura (Telefonica), but also to improve processes and optimize resources, such as detecting anomalies in machines or a logistics chain, detecting fraud, etc. Actually, we talk about the application of Machine Learning techniques for these purposes, although it is easier to recognize it by its generalization "Artificial Intelligence", or we could include it within the term "Machine Intelligence". Many of…

11
Jan
The Deep Learning Hype
  • Alfonso Ibañez
  • 1757 Views
  • 2 Comments
  • Algoritmos . Big Data . Computación . Data . Data Science . Data Scientists . Deep Learning . Deep Learning Hype . Fiebre Deep Learning . IA . Inteligencia Artificial . Machine Learning . Neural Networks . Redes Neuronales .

In the era of Big Data a day does not pass by without us reading some news about Artificial Intelligence, Machine Learning or Deep Learning, never knowing what they refer to. The "experts" of the sector mix and exchange the terms with all naturalness, and only contribute to their hype. The simple fact of mentioning them catches the attention of investors and convinces them that these techniques have an almost magical power. Machine Learning is a scientific discipline coming from Artificial Intelligence, that studies how systems can be programmed to learn and improve with experience without human intervention. To address this problem, new paradigms emerge daily that allow the discovery of knowledge based on specific data deriving from solid statistical…

16
Aug
Anticipating Customer Churn through Levers of Retention
  • Rubén Granados
  • 2919 Views
  • 0 Comment
  • Big Data . Churn Prediction . Data Science . Fuga de Clientes . Machine Learning . Palancas de Retencion .

Identification and analysis of signs of customer churn Knowing which customers might not continue as such has been the objective of classic customer churn models, which final output consisted of the probability of loss associated with each customer over a specific temporary time range. However, once we know the customer is going to leave, we must ask ourselves: What can we do to keep them? And taking it even further: What can we do to keep the customer from even considering leaving? Preventive Measures for Customer Churn in the Banking Sector At Synergic Partners, we have carried out a project for one of the largest banking entities in Spain responding to these questions with a methodology based on the combination…

30
May
Improving Effectiveness at a Call Center with Machine Learning
  • Víctor Gonzalez
  • 3719 Views
  • 0 Comment
  • Algorithms . Big Data . Data Science . Machine Learning . Procesamiento de Lenguaje Natural .

Understanding our clients and giving the best response to meeting their needs in the shortest amount of time possible is key to improving satisfaction and engagement with the company. The problem begins when the number of clients is high and we are receiving hundreds or thousands of messages per day. In this situation, we have two problems to solve. First, we have to prioritize which messages we are going to respond first and, second, we have to understand what it is that they are saying. It is clear that some messages will be more important or more urgent than others and that it will not always be easy to prioritize. To make things easier, we can use Machine Learning techniques…

08
Nov
A Brief History of Machine Learning
  • Víctor Gonzalez
  • 4548 Views
  • 0 Comment
  • Big Data . ciencia de los datos . Data Science . Machine Learning .

As members of the Machine Learning community, it would be a good idea for us all to have an idea of the history of the sector we work in. Although we are currently living through an authentic boom in Machine Learning, this field has not always been so prolific, going through periods of high expectations and advances as well as “winters” of severe stagnation. Birth [1952 - 1956] 1950 — Alan Turing creates the “Turing Test” to determine whether or not a machine is truly intelligent. In order to pass the test, the machine must be capable of making a human believe that it is another human instead of a computer. 1952 — Arthur Samuel writes the first computer program…

17
Sep
Warnings about normalizing data
  • Santiago Morante
  • 4051 Views
  • 13 Comments
  • Algorithms . Algoritmos . Analítica Avanzada . Big Data . Blog Synergic . Data . Data Normalization . Data Science . datos . Machine Learning . Normalización de Datos .

For many machine learning algorithms, normalizing the data of analysis is a must. A supervised example would be neural networks. It is known that normalizing the input data to the networks improve the results. If you don't believe me it's ok (no offense taken), but you may prefer to believe Yann Le Cunn (Director of AI Research in Facebook and founding father of convolutional networks) by checking section 4.3 of this paper. You can catch up the idea with the first sentence of the section: Convergence [of backprop] is usually faster if the average of each input variable over the training set is close to zero. Among other things, one reason is that when the neural network tries to correct…

09
May
Synergic Partners takes part at #RETINA 2016, held by El País
  • Synergic Partners
  • 1344 Views
  • 0 Comment
  • Carme Artigas . digital transformation . innovación . Inteligencia Artificial . internet of things . IoT . Machine Learning .

Digitalization is changing the business model RETINA, an event organized by El País, will be held May 10 and 11 at the Palacio Municipal de Congresos, Campo de las Naciones in Madrid. RETINA is an essential event for those professionals called to lead the digital transformations of their organizations. It is a forum at which entrepreneurs, business directors, investors and public managers can share experiences and business opportunities related to new technologies and the new digital environment. On Tuesday, May 10, Carme Artigas, CEO and co-founder of Synergic Partners, will give a speech focused on Artifical Intelligence and Machine Learning. There will be a content room in the innovation area – an agenda focused on entrepreneurship and the Internet of…

28
Jan
XGBoost
  • Synergic Partners
  • 5197 Views
  • 0 Comment
  • Kaggle . Machine Learning . XGBoost .

In Kaggle machine learning competitions, two techniques tend to be dominant: the use of groupings of decision trees for structured data and neural networks when the data includes images or sound. Traditionally, Random Forest dominated competitions in structured data, but another algorithm has recently surpassed it in these competitions: Gradient Boosted Trees. Like RF, GBT classifies examples through the use of a grouping of decision trees. In the case of the latter, the trees are constructed sequentially, adding at each iteration the tree that best compensates for the errors in the other trees. This method is called gradient because the model evolves tree by tree towards a minimum of error. The tool used in these cases is called XGBoost, an…

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