classification


amazon-brings-artificial-intelligence-to-cloud-storage-to-protect-customer-data

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The new service dubbed Amazon Macie relies on Machine Learning to automatically discover, classify, and protect sensitive data stored in AWS. This service reports potential risks involved with the stored data, its permissions, and access patterns. Chris Vickery, a cyber risk security analyst from UpGuard, discovered several passwords and keys belonging to Booz Allen employees working on the NGA project in publicly accessible Amazon S3 Buckets. Though Amazon S3 is the only data source supported by Macie, AWS is expected to bring other services such as Amazon RedShift, Amazon RDS, Amazon Elastic File System into the fold.


What is Machine Learning?

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Machine learning is perhaps the principal technology behind two emerging domains: data science and artificial intelligence. Whether it's manufacturing or logistics, efficiency can be improved by automating components of the processes to improve the flow of goods. In these processing pipelines, manufacturing, logistics or data management, the overall pipeline normally also requires human intervention from an operator. In information processing settings these atoms require emulation of our cognitive skills.


Amazon Brings Artificial Intelligence To Cloud Storage To Protect Customer Data

#artificialintelligence

The new service dubbed Amazon Macie relies on Machine Learning to automatically discover, classify, and protect sensitive data stored in AWS. This service reports potential risks involved with the stored data, its permissions, and access patterns. Chris Vickery, a cyber risk security analyst from UpGuard, discovered several passwords and keys belonging to Booz Allen employees working on the NGA project in publicly accessible Amazon S3 Buckets. Though Amazon S3 is the only data source supported by Macie, AWS is expected to bring other services such as Amazon RedShift, Amazon RDS, Amazon Elastic File System into the fold.


Global Bigdata Conference

#artificialintelligence

The new service dubbed Amazon Macie relies on Machine Learning to automatically discover, classify, and protect sensitive data stored in AWS. This service reports potential risks involved with the stored data, its permissions, and access patterns. Chris Vickery, a cyber risk security analyst from UpGuard, discovered several passwords and keys belonging to Booz Allen employees working on the NGA project in publicly accessible Amazon S3 Buckets. Based on the sensitivity and the criticality of the data discovered, Macie classifies the document into one of the predefined risk levels.


The Hitchhiker's Guide to Machine Learning in Python

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Decision trees are becoming increasingly popular and can serve as a strong learning algorithm for any data scientist to have in their repertoire, especially when coupled with techniques like random forests, boosting, and bagging. Support vector machines, also known as SVM, are a well-known supervised classification algorithm that create a dividing line between the your differing categories of data. K-Means is a popular unsupervised learning classification algorithm typically used to address the clustering problem. The algorithm begins with randomly selected points and then optimizes the clusters using a distance formula to find the best grouping of data points.


How do you solve a classification machine learning problem using R?

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This guide will introduce you to the fundamentals of the classification machine learning problem using R and how you can apply this into data sets that will generate value for your business. In this classification problem we want to predict which employees will leave the firm and which employees would stay with the firm based on various factors. Now that we understand how the tree works let's shuffle our HR analytics data and split it into training and test sets with the code shown below: We then split the data into training and test sets with 70% of the data being assigned to the training set and 30% of the data being assigned into the test set. The next step is to predict the outcome of training the "train" dataset using the model using the "test" dataset.


From 0 to 1: Machine Learning, NLP & Python-Cut to the Chase

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The course is shy but confident: It is authoritative, drawn from decades of practical experience -but shies away from needlessly complicating stuff. You can put ML to work today: If Machine Learning is a car, this car will have you driving today. The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.


Machine Learning Classification Algorithms using MATLAB

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This course is designed to cover one of the most interesting areas of machine learning called classification. Following that we will look into the details of how to use different machine learning algorithms using MATLAB. Specifically, we will be looking at the MATLAB toolbox called statistic and machine learning toolbox.We will implement some of the most commonly used classification algorithms such as K-Nearest Neighbor, Naive Bayes, Discriminant Analysis, Decision Tress, Support Vector Machines, Error Correcting Ouput Codes and Ensembles. Though it does not cover Matlab toolboxes etc, it is still a great basic introduction for the platform.


Machine Learning is Fun Part 8: How to Intentionally Trick Neural Networks

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Check out the full series: Part 1, Part 2, Part 3, Part 4, Part 5, Part 6, Part 7 and Part 8! To build this, we'll train a deep convolutional neural network to tell prohibited items apart from allowed items and then we'll run all the photos on our site through it. Here's how that looks on a graph for a simple two-dimensional classifier that's learned to separate green points (acceptable) from red points (prohibited): Right now, the classifier works with 100% accuracy. In image classification with deep neural networks, each "point" we are classifying is an entire image made up of thousands of pixels.


sekwiatkowski/komputation

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Komputation is a neural network framework for the JVM written in the Kotlin programming language. See the TREC demo for more details.