AI News, 6 Top Big Data and Data Science Trends 2017
- On Sunday, June 3, 2018
- By Read More
6 Top Big Data and Data Science Trends 2017
Recently we stepped in the 2017 year, and it’s time to draw the conclusion about 2016.
This process is driven by increased collaboration and flexibility, as well as reducing the complexity of administration and configuration of computing resources.And majority of the top cloud providers developed their own offering of Machine Learning services in a cloud.
This step allows organizations to leverage machine learning technology, without massive investments and needs to employ large data science teams.
Here are main examples of such machine learning and AI as a service (MLaaS and AIaaS) providers: Those working with the data know very well that data is useless if it is not efficiently analyzed and turned into insights, which is, in fact, support decision-making process.
According to recent studies, the percent of users using Spark on the public cloud (61%) was higher than the percent using Hadoop YARN (36%) and this trend will continue in 2017.
One of the recent trends in security is increased usage of machine learning algorithm, including deep learning for detection of anomalies and other fields of data science security in various business domains.
In the future, there may occur a lot of new types of attacks, and thus the requirements for cyber security are getting more complicated, and security specialists will need to adapt to the new threats.
Deep learning gets a lot of attention in 2016, as many noticeable results were achieved by using it for many important applications, such as machine translation and other forms of language processing, Automatic Image Caption Generation, Object Classification and Detection in Images, Facial Recognition and Automatic Game Playing.
Despite the fact that the bots have been existing for a long time, only now the AI development has reached a level where it became possible to create some advanced products, many of which utilize machine learning.
Some of the prominent examples of conversational AI we can see in such products as Google Assistant and Siri for iOS, which have become an almost indispensable product for users of smartphones and has already gone far beyond just a fun application or quirks users.
This year is going to be “The Year of Intelligence” as we see that AI and machine learning applications are going mainstream and contributes to every part of organization and business areas and becoming one of the key competitive advantages for companies which integrate machine learning into its operations.
We are not pretending this to be an ultimate list, as so many things are evolving quickly in technology realm, so we encourage you to share your vision about main trends for data and data science field in the comments section below.
- On Monday, September 23, 2019
Sundar Pichai: How machine learning & deep learning improved technologies
Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning ...
Tech Trends 2017: Machine intelligence advances analytics
Nitin Mittal, principal, Deloitte Consulting LLP, shares how machine learning drives insights for decision making, worker augmentation, and task automation.
Why Machine Learning is The Future? | Sundar Pichai Talks About Machine Learning
Why Machine Learning is The Future? | Sundar Pichai Talks About Machine Learning ...
Machine Learning and Human Bias
As researchers and engineers, our goal is to make machine learning technology work for everyone.
What is machine learning and how to learn it ?
Machine learning is just to give trained data to a program and get better result for complex problems. It is very close to data ..
Mike Innes - Julia: A Fresh Approach to Machine Learning
Filmed at PyData London 2017 Description Julia's well-known combination of ease-of-use, performance and powerful features make it uniquely suited to the ...
How to Ruin Your Business with Data Science and Machine Learning
Past, Present and Future of AI / Machine Learning (Google I/O '17)
We are in the middle of a major shift in computing that's transitioning us from a mobile-first world into one that's AI-first. AI will touch every industry and transform ...
Machine Learning with scikit learn Part One | SciPy 2017 Tutorial | Andreas Mueller & Alexandre Gram
Machine learning is the task of extracting knowledge from data, often with the goal of generalizing to new and unseen data. Applications of machine learning ...