Disruptive technologies– an umbrella term for technical disciplines that are currently said to transform the digital landscape. The spearheads of this transformation are artificial intelligence (AI), data science, and machine learning (ML). The best part is these technologies are also interrelated. In technical parlance, machine learning is a dynamic application of AI that empowers the machines to learn from data provided and improve the model accuracy levels. And data scientists mine data to extract insights and forecast future trends based on the data collected from machine learning or AI models.

Disruptive technologies– an umbrella term for technical disciplines that are currently said to transform the digital landscape. The spearheads of this transformation are artificial intelligence (AI), data science, and machine learning (ML). The best part is these technologies are also interrelated. In technical parlance, machine learning is a dynamic application of AI that empowers the machines to learn from data provided and improve the model accuracy levels. And data scientists mine data to extract insights and forecast future trends based on the data collected from machine learning or AI models.

We discuss the use of Machine Learning pipeline architectures for implementing production ML applications, and in particular we review Google's experience with TensorFlow Extended (TFX). An ML application in production must address all of the issues of modern software development methodology, as well as issues unique to ML and data science. Most of the focus in the ML community is on research, which is exciting and important. Equally important however is bringing that research to production applications to solve real-world problems, but the issues and approaches for doing that are often poorly understood. An ML application in production must address all of the issues of modern software development methodology, as well as issues unique to ML and data science.

When I was in grad school it was called statistics. A few years later I told people I did machine learning and after seeing the confused look on their face I changed that to data science which excited them. More years passed, and without changing anything I do, I now practice AI, which seems scary to some people and somehow involves ML. We'll touch upon key concepts and see a little bit of code in action to get a sense of what is happening in ML, AI or whatever else we want to call the field.

We look forward to meeting you!!

In today's data driven business world, catchphrases like data analytics, data science (DS), artificial intelligence (AI), machine learning (ML) and deep learning (DL) are terms swirling around boardroom discussions. These digital concepts are increasingly becoming imperative for CIOs and IT leaders in critical decision-making process. Often times these terminologies are loosely or interchangeably referred, without deciphering the real meaning and how individually and collectively they impact businesses. In order to exploit the true potential of these technologies, it is critical for companies to demystify the ambiguity surrounding them. In this blog, we attempt to demystify the terminologies, explain the comprehensiveness of what data science and data analytics is, what artificial intelligence (AI) embodies, and how technologies like Machine Leaning (ML) and Deep Learning (DL) are evolving fast, stimulating AI adoption on a broader scale.

The below lists various resources related to careers in artificial intelligence industry. Below are some resources related to the having a career in the AI industry. Jobs for R-users – A job board for people and companies looking to hire R users (for programming, data science, teaching). Jobs for R-users – A job board for people and companies looking to hire R users (for programming, data science, teaching). Open Data Services is a new workers co-operative.

The below lists various resources related to careers in artificial intelligence industry. Below are some resources related to the having a career in the AI industry.