How Engineering Will Change Machine Learning, Deep Learning In AI, Women In Data Science, Data scientists Job Role and How IoT Can Feed The World.
There are few certainties in data science — libraries, tools, and algorithms constantly change as better methods are developed. However, one trend that is not going away is the move towards increased levels of automation.
This is made possible by the extraordinary amount of data we collect and consume—data is the fuel for deep-learning models. For more on what deep learning is please check out my previous post here.
With data science being one of the fastest growing job categories in the world, it’s never been a better time for women to enter the field.
Yet the terms “data science” and “data scientist” aren’t always easily understood, and are used to describe a wide range of data-related work.
10 Amazing Examples Of How Deep Learning AI Is Used In Practice? - How could you possibly get machines to learn like humans? And, an even scarier notion for some, why would we want machines to exhibit human-like behavior? Here, we look at 10 examples of how deep learning is used in practice that will help you visualize the potential.
What to know about the phenomenon that is data science, how women can excel at it - And these are extremely well-paid jobs. Some have starting salaries for graduates of $100k, with the average starting salary around $80k. The majority of salaries are on average between $130k to $180k for data scientists in Australia, but it’s not unheard of to earn $230k+.
What, exactly, is it that data scientists do? - What, exactly, is it that data scientists do? As the host of the DataCamp podcast DataFramed, I have had the pleasure of speaking with over 30 data scientists across a wide array of industries and academic disciplines. Among other things, I’ve asked them about what their jobs entail.
https://hbr.org/2018/08/what-data-scientists-really-do-according-to-35-data-scientists
How The Internet Of Things Could Help Feed The World - There has been a flurry of attention to creating devices ranging from thermostats to wearables that “talk” to each other, analyze information and perform tasks.
Why Automated Feature Engineering Will Change the Way You Do Machine Learning - Automated feature engineering will save you time, build better predictive models, create meaningful features, and prevent data leakage.
https://www.kdnuggets.com/2018/08/automated-feature-engineering-will-change-machine-learning.html
“In the end you should only measure and look at the numbers that drive action, meaning that the data tells you what you should do next.” – Alex Peiniger, CEO at Quintly