[unable to retrieve full-text content]dSPP is the world first interactive database of proteins for AI and Machine Learning, and is fully integrated with Keras and Tensorflow. You can access the database at peptone.io/dspp
Original Post: The world’s first protein database for Machine Learning and AI
[unable to retrieve full-text content]Also 10 Free Must-Read Books for #MachineLearning and #DataScience; #Keras implementation of a simple Neural Net module for relational reasoning; Applying #deeplearning to real-world problems
Original Post: Top KDnuggets tweets, Jun 14-20: 5 EBooks to Read Before Getting into A Data Science or Big Data Career
[unable to retrieve full-text content]Broadly speaking, machine learners are computer algorithms designed for pattern recognition, curve fitting, classification and clustering. The word learning in the term stems from the ability to learn from data.
Original Post: Making Sense of Machine Learning
[unable to retrieve full-text content]In the past, ML learning hasn’t had as much success in cyber security as in other fields. Many early attempts struggled with problems such as generating too many false positives, which resulted mixed attitudes towards it.
Original Post: Does Machine Learning Have a Future Role in Cyber Security?
[unable to retrieve full-text content]Here are some of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop – only $10 until June 21, 2017.
Original Post: Best Data Science Courses from Udemy (only till June 21)
[unable to retrieve full-text content]Machine learning algorithms are used everywhere these days: from medical science to self driven cars. Here we explain how it helps to solves challenges in manufacturing of self driven cars.
Original Post: The Machine Learning Algorithms Used in Self-Driving Cars
[unable to retrieve full-text content]What is it that distinguishes neural networks that generalize well from those that don’t? A satisfying answer to this question would not only help to make neural networks more interpretable, but it might also lead to more principled and reliable model architecture design.
Original Post: Understanding Deep Learning Requires Re-thinking Generalization
Posted by Jonathan Huang, Research Scientist and Vivek Rathod, Software Engineer(Cross-posted on the Google Open Source Blog)At Google, we develop flexible state-of-the-art machine learning (ML) systems for computer vision that not only can be used to improve our products and services, but also spur progress in the research community. Creating accurate ML models capable of localizing and identifying multiple objects in a single image remains a core challenge in the field, and we invest a significant amount of time training and experimenting with these systems. Last October, our in-house object detection system achieved new state-of-the-art results, and placed first in the COCO detection challenge. Since then, this system has generated results for a number of research publications1,2,3,4,5,6,7 and has been put to work in Google products such as NestCam, the similar items and style ideas feature in Image Search and…
Original Post: Supercharge your Computer Vision models with the TensorFlow Object Detection API
[unable to retrieve full-text content]Machine Learning in Real Life: Tales from the Trenches; Is Regression Analysis Really Machine Learning?; Implementing Your Own k-Nearest Neighbour Algorithm Using Python; Building Simple Neural Networks - TensorFlow for Hackers.
Original Post: Top KDnuggets tweets, Jun 07-13: Is Regression Analysis Really Machine Learning?
[unable to retrieve full-text content]Recently, PSL Research University launched a one-week course combining theoretical lectures and practical sessions. 115 students from various backgrounds and skill levels were enrolled; something quite spectacular happened during the week: Students have achieved an astounding level of score improvement – in just three afternoons.
Original Post: Open Innovation and Crowdsourcing in Machine Learning – Getting premium value out of data