Machine Learning Artificial Intelligence Stock And Forex Trading System P1

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In the next few posts we are going to discuss the design, development and testing of a machine learning artificial intelligence stock and forex trading system. Machine Learning is a new frontier. Machine learning is a new name for data mining using statistical algorithms.


Photonic Time Stretch Microscopy Combined with Artificial Intelligence Spots Cancer Cells in Blood

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UCLA researchers have developed a new laser-based technology to rapidly screen blood samples for the presence of cancer cells. The label-free system measures 16 different physical characteristics of each cell and analyzes the data to identify whether the cell is cancerous. Not having to introduce any labeling chemicals and being gentle on the cells, the technique leaves the cells alive and available for further inspection using other means. It relies on a photonic time stretch microscope and a computer that runs deep learning artificial intelligence algorithms. The microscope can take millions of images per second thanks to unusual optics that produce high quality shots even at this speed.


Atlanta Artificial Intelligence Meetup

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This is a single day course from 9:00am to 2:00pm. You will need to bring your laptop and have python, TensoFflow 1.0 and pandas installed before the class. You can find the instructions here. If you have any difficulties let us know before the day of the training and we will provide you with support. We will be running two parallel sessions, one for new users who have minimal or no experience with TensorFlow and another one for advanced users.


Deep Learning: Definition, Resources, Comparison with Machine Learning

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Deep learning is sometimes referred to as the intersection between machine learning and artificial intelligence. It is about designing algorithms that can make robots intelligent, such a face recognition techniques used in drones to detect and target terrorists, or pattern recognition / computer vision algorithms to automatically pilot a plane, a train, a boat or a car. Many deep learning algorithms (clustering, pattern recognition, automated bidding, recommendation engine, and so on) -- even though they appear in new contexts such as IoT or machine to machine communication -- still rely on relatively old-fashioned techniques such as logistic regression, SVM, decision trees, K-NN, naive Bayes, Bayesian modeling, ensembles, random forests, signal processing, filtering, graph theory, gaming theory, and many others. Some are new, such as indexation algorithms to automate digital publishing, improve search engines, or create and manage large catalogs such as Amazon's product listing. As a result, many deep learning practitioners call themselves data scientist, computer scientist, statistician, or sometimes engineer.


Deep Learning: Definition, Resources, Comparison with Machine Learning

#artificialintelligence

Deep learning is sometimes referred to as the intersection between machine learning and artificial intelligence. It is about designing algorithms that can make robots intelligent, such a face recognition techniques used in drones to detect and target terrorists, or pattern recognition / computer vision algorithms to automatically pilot a plane, a train, a boat or a car. Many deep learning algorithms (clustering, pattern recognition, automated bidding, recommendation engine, and so on) -- even though they appear in new contexts such as IoT or machine to machine communication -- still rely on relatively old-fashioned techniques such as logistic regression, SVM, decision trees, K-NN, naive Bayes, Bayesian modeling, ensembles, random forests, signal processing, filtering, graph theory, gaming theory, and many others. Some are new, such as indexation algorithms to automate digital publishing, improve search engines, or create and manage large catalogs such as Amazon's product listing. As a result, many deep learning practitioners call themselves data scientist, computer scientist, statistician, or sometimes engineer.