Data Science News

Data Science

27 Amazing Data Science Books Every Data Scientist Should Read
Every person has their own way of learning. What helped me break into data science was books. There is nothing like opening your mind to a world of knowledge condensed into a few hundred pages. There is a magic and allure to books that I have never found ... @ 2019-01-17T06:06:00
Data Scientist: A Hot Job That Pays Well
... least six years now and college students majoring in computer science are on the rise. What do we know about data scientists? They typically are fluent in one or more programming languages ... @ 2019-01-17T05:43:00
How to answer Data Science Interview Coding Questions?
At Acing AI, I have been hard at work to help Data Scientists get into Data Science roles. All tech companies hiring today for this position usually start with a coding test. This article aims to ... @ 2019-01-17T10:06:00

Artificial Intelligence (AI)

Our Evolving Relationship With Artificial Intelligence And Health Care
Dekel Gelbman is CEO of FDNA, an AI and digital health company that develops technologies and SaaS platforms in the clinical genomics space. We have created a world where our need to perform certain tasks has been greatly alleviated. But for a society ... @ 2019-01-17T13:30:00
Amazon sets conference on robotics, artificial intelligence
Amazon will host a June conference on robotics and artificial intelligence, showcasing some of the technology used for its Alexa digital assistant Amazon announced plans Thursday to hold a ... @ 2019-01-17T17:23:00
Artificial intelligence applied to the genome identifies an unknown human ancestor
Jaume Bertranpetit, researcher at the Institute of Evolutionary Biology, and Oscar Lao, researcher at the Centre for Genomic Regulation, co-led the study. Credit: Pilar Rodriguez By combining deep ... @ 2019-01-17T14:01:00

Extra - If You Have Time

Neural Networks | A beginners guide
Unsupervised machine learning has input data X and no corresponding ... affects feedforward networks that use back propagation and recurrent neural network. This is known as deep-learning. Hardware-based designs are used for biophysical simulation and ... @ 2019-01-17T14:41:00
Best of arXiv.org for AI, Machine Learning, and Deep Learning – December 2018
Particular focus is on the aspects related to generalization and how deep RL can be used for practical applications. The reader is assumed to be familiar with basic machine learning concepts. Recurrent neural networks (RNNs) are powerful architectures to ... @ 2019-01-17T03:23:00
How to Accelerate Learning of Deep Neural Networks With Batch Normalization
Batch normalization is a technique designed to automatically standardize the inputs to a layer in a deep learning neural network. Once implemented, batch normalization has the effect of dramatically accelerating the training process of a neural network ... @ 2019-01-17T20:20:00