[unable to retrieve full-text content]We rethink Asimov’s 3 law of robotics to help companies moving to unsupervised machine learning and realize 100% automated predictive information governance (PIG).
Original Post: 3 Laws of Machine Learning
[unable to retrieve full-text content]I learned how important to understand data before running algorithms, how important it is to know the context and the industry before jumping on getting insights, how it is very easy to make models but tough to get them to work for you, and finally, how it only takes one line of code to run linear regression on your dataset.
Original Post: It Only Takes One Line of Code to Run Regression
[unable to retrieve full-text content]Here is useful advice about moving from academia into data science after completing a PhD in a natural science.
Original Post: Learning git is not enough: becoming a data scientist after a science PhD
[unable to retrieve full-text content]We examine the implications of trends in hiring market, including the growth of quantitative Initiatives, blurring of the lines between Predictive Analytics and Data Science Professionals, and more .
Original Post: 4 Major Trends Influencing the 2017 Predictive Analytics Hiring Market
[unable to retrieve full-text content]Social media and machine learning concepts are transforming self-service data prep into a collaborative data marketplace.
Original Post: Social Media and Machine Learning Transform Self-service Data Prep
[unable to retrieve full-text content]Instead of arguing about Python vs R I will examine the best practices of integrating both languages in one data science project.
Original Post: Best practices of orchestrating Python and R code in ML projects
[unable to retrieve full-text content]Edge analytics is the collection, processing, and analysis of data at the edge of a network either at or close to a sensor, a network switch or some other connected device.
Original Post: Edge Analytics – What, Why, When, Who, Where, How?
[unable to retrieve full-text content]Fake news is an important issue on social media. This article provides an overview of fake news characterization and detection in Data Science and Machine Learning research.
Original Post: A Quick Guide to Fake News Detection on Social Media
[unable to retrieve full-text content]The relevance of a full stack developer will not be enough in the changing scenario of things. In the next two years, full stack will not be full stack without AI skills.
Original Post: How I started with learning AI in the last 2 months
[unable to retrieve full-text content]Today AI is everywhere, from virtual assistants scheduling meetings, to facial recognition software and increasingly autonomous cars. We review 5 main factors for the successful AI implementation.
Original Post: 5 overriding factors for the successful implementation of AI