An analyst report offers an unbiased, side-by-side, third-party evaluation of the technology in the market. These analysts know how to put the vendors through the paces and require proof of any claims that are made.
Teknoloji dur durak tanımıyor, günbegün yeni buluşlarla, atılımlarla ve daha nicesiyle tanışıyoruz. Daha da önemlisi, bunu artık anlık olarak yapıyoruz. İnternet çağının katkılarıyla, Türkiye’de yaşayan bir kişi dünyanın herhangi bir yerinde, dün yapılmış bir çalışmayı hemen kişisel bilgisayarının rahatlığıyla okuyabiliyor. Tabii ki, bu kadar hızlı gelişmenin artıları olurken eksileri de
The popular image of data scientists is very much a bit of a geek or nerd. However, that’s not strictly accurate. It may not be – as Harvard Business Review famously suggested – the sexiest job of the 21st century. But it is a long way from the perceived world
Decision trees are a fundamental machine learning technique that every data scientist should know. Luckily, the construction and implementation of decision trees in SAS is straightforward and easy to produce. There are simply three sections to review for the development of decision trees: Data Tree development Model evaluation Data The
An embedding model is a way to reduce the dimensionality of input data, such as images. Consider this to be a type of data preparation applied to image analysis. When an embedding model is used, input images are converted into low-dimensional vectors that can be more easily used by other computer vision tasks. The key to good embedding is to train the model so that similar images are converted to similar vectors.
Ever since automated machine learning has entered the scene, people are asking, "Will automated machine learning replace data scientists?"
Let's talk about using DLPy to model employee retention through a survival analysis model. Survival analysis is used to model time-to-event. Examples of time-to-event include the time until an employee leaves a company, the time until a disease goes into remission, or the time until a mechanical part fails. The
This blog is a part of a series on the Data Science Pilot Action Set. In this blog, we discuss updates to Visual Data Mining and Machine Learning with the release of Viya 3.5. In the middle of my blog series, SAS released Viya 3.5. Included in Viya 3.5 was the
Computer vision can augment radiologists and make the image interpretation process cheaper, faster and more accurate. The ultimate goal is to achieve a better patient outcome facilitated by the use of computer vision.
This series of videos spotlights a very powerful API that lets you use Python while also having access to the power of SAS Deep Learning.
The concept of analysing increasingly complex data to inform decision making is very relevant to policing today. Data science can and should support modern police forces to serve their communities. But what do we mean by data science and data scientists? One dictionary definition of a data scientist is: “a
At the end of my SAS Users blog post explaining how to install SAS Viya on the Azure Cloud for a SAS Hackathon in the Nordics, I promised to provide some technical background. I ended up with only one manual step by launching a shell script from a Linux machine
Data Scientists verbringen eine Menge Zeit mit Daten. Dabei gilt immer – von der Anwendung von Machine-Learning-Modellen bis hin zum Trainieren von KI-Modellen: Mit der Datenqualität stehen und fallen die Ergebnisse. Analytics und Data Science stellen jedoch nicht nur Ansprüche an Datenqualität. Sie können auch dazu beitragen, diese zu verbessern.
Si reconoces que el análisis de datos es fundamental para el éxito de tu organización, entre el 28 de abril y el 1 de mayo tienes que estar en Dallas, Texas, la sede del evento más importante del ámbito de la analítica avanzada. ¿Qué motivos justificarían el viaje? Podríamos señalar
I don't know about you, but when I read challenges like: Detecting hidden heart failure before it harms an individual Can SAS Viya AI help to digitalize pension management? How to recommend your next adventure based on travel data How to use advanced analytics in building a relevant next best
Amidst the growing popularity of modern machine learning and deep learning techniques, one of the biggest challenges is the ability to obtain large amounts of training data suitable for your use case. This post discusses how the analytical approach for Named Entity Recognition (NER) can help.
Diese Frage bekomme ich von Nicht-Data-Scientists immer häufiger gestellt. Und es ranken sich viele Meinungen und Mythen um diese Expertengruppe. Genau aus diesem Grund habe ich mich mit Simon Greiner, einem angehenden Data Scientist und erfahrenen IT-Berater, unterhalten. Ein Mythos über Data Scientists: sie lesen keine Bücher mehr. Stimmt nicht!
AI seems to be mentioned everywhere these days. But how can AI be used in day-to-day work? Here, Katherine Taylor explains an example of "practical AI" in banking using SAS Visual Data Mining and Machine Learning. She'll explore more business problems and industries in future posts.
“No sólo piense como un científico de datos, conviértase en uno”. Esta afirmación puede marcar una gran diferencia entre sobresalir como un profesional analítico en la era de la transformación digital, o quedarse estancado sin explotar sus capacidades y perdiendo oportunidades de crecer, influir en las decisiones de su organización
Data scientists need good skills in communication, data mining, data wrangling and more. Joyce Norris-Montanari explains.
Phil Simon chimes in with some tips on how to set these folks loose.
Mein Name ist Daniel und ich bin in der vierten Klasse. Diese Woche wurden die Eltern in meine Schule eingeladen, um uns etwas über ihre Arbeit zu erzählen. Und mein Vater war mit dabei. Am Anfang war ich etwas unsicher, ob ich mich darüber freuen sollte. Denn wenn sein Vortrag
El popular dicho español ‘El que mucho abarca poco aprieta’ ha cobrado gran relevancia en la era del análisis de datos. Cuando los data scientists, data analysts, y analistas en general realizan modelos para predecir comportamientos, tendencias, patrones, etc. se enfrentan ante el desafío de abarcar lo suficiente para apretar
Several weeks ago, I wrote about practical advice from a Chief Data Scientist in my blog “From Aristotle to Pi: Practical advice from a chief data scientist.” Now I want to offer my advice as a newbie trying to navigate through machine learning concepts and how to code them. Over
Getting started with SAS Viya and RStudio -- making the connection, and submitting my first commands via CAS actions.
In fast jedem Vortrag zum Thema Analytics geht es irgendwann auch um Talentsuche und den vielbeschworenen Fachkräftemangel. Diskutiert wurden eben diese Herausforderungen auch beim CI Connection Circle von SAS in Nizza. Welche Maßnahmen Unternehmen ergreifen sollten, um begabte Datenspezialisten anzuziehen und nachhaltig an sich zu binden, war bereits in diesem
2018, el año de la economía analítica Imaginemos que para formar una beta que crece continuamente está basada en datos generados diariamente por una organización –a partir de sus actividades productivas, transacciones y relaciones con clientes y proveedores, por ejemplo. Ese cúmulo de información no tiene ninguna valía per se;
Meetup ist ein Online-Social-Networking-Service mit einem kleinen Unterschied zu Facebook, Instagram, LinkedIn & Co. Das Format ist dazu gedacht, Face-to-Face-Treffen zu interessanten Themen zu organisieren. Die Offline-Welt ist also ein elementarer Bestandteil. Selbstorganisiert und thematisch vielfältig Gruppen gibt es zu fast jedem Thema: Bücherclubs, Socialising, R-Nutzer, Unternehmer oder künstliche Intelligenz
Es hat eine lange Tradition, teilweise freiwillig, teilweise aus der Not geboren: Dinge selbst in die Hand zu nehmen. „Do-it-yourself – Selbst ist der Mann/die Frau – wenn-du-willst-das-etwas-erledigt-wird-dann-mach-es-selbst“. Oder halt IKEA-Möbel, Brotbackautomaten beim Discounter, BI-as-a-self-Service, Online-Banking … Mit der Kommentarfunktion dürfen Sie später die Liste gerne ergänzen! Und das hat
Neil Harbisson is completely colour-blind. He sees the world in greyscale. But that does not mean that Neil does not experience colour. Since 2004, he has worn an electronic ‘eye’ that turns the colours into sounds by wavelength. He now experiences the world as a series of tones. He dresses
