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This video is about 4 minute. CNN's Maggie Lake gets a rare look inside the super-fast trading industry.
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The Idiots Guide to High Frequency TradingHigh Frequency Trading Explained (HFT)
Dave Fry, founder and publisher of ETF Digest, and Steve Hammer, founder of HFT Alert, discuss high frequency trading operations, fundamentals, the difference between algorithmic trading and high frequency trading, fluttering, latency and the role high frequency trading had in the May stock market flash crash in 2010.
Learning ONNX for trading
Forum on trading, automated trading systems and testing trading strategies
Learning ONNX for trading
MetaQuotes , 2023.03.30 17:44
1. ONNX Runtime
This article talks about the Open Neural Network Exchange (ONNX) project , which is an open format for presenting traditional and deep learning models. It also describes ONNX Runtime, a high-performance engine for running these models.
ONNX Runtime is fully compliant with the operators defined in the ONNX specification and runs on both CPU and GPU on many platforms including Linux, Windows and Mac.
Provides a step-by-step guide to converting, loading, and running a model using ONNX Runtime in Azure ML and demonstrates its potential benefits, including improved performance and prediction performance for various models.
It is also encouraged to try ONNX and contribute to the growing ONNX community.
Learning ONNX for trading
Forum on trading, automated trading systems and testing trading strategies
Learning ONNX for trading
MetaQuotes , 2023.03.30 17:44
2. Converting Models to #ONNX Format
Describes various ways to convert machine learning models to the ONNX format for use with the ONNX Runtime. ONNX is compatible with many popular machine learning libraries such as PyTorch, TensorFlow and Scikit-Learn.
To convert a model to the ONNX format, you must use the appropriate conversion library, and then create an ONNX model using this library. This allows the model to be used with ONNX Runtime, which improves its performance and makes it compatible with multiple platforms.
Examples of converting models to the ONNX format using PyTorch and TensorFlow are given.
Learning ONNX for trading
Forum on trading, automated trading systems and testing trading strategies
Learning ONNX for trading
MetaQuotes , 2023.03.30 17:45
3. ONNX – open format for machine learning models
Describes the ONNX format, which is an open format for storing machine learning models . It is possible to convert models from various frameworks to the ONNX format, which ensures their compatibility and ease of use.
Examples of compatible formats such as TensorFlow, PyTorch, Keras, and scikit-learn are provided, and the benefits of using ONNX are discussed, such as faster model execution time and optimized performance on specific hardware.
In the next video, the author promises to show how to convert a model from Keras to ONNX format and test it on the example of image classification and image segmentation problems.
Learning ONNX for trading
Forum on trading, automated trading systems and testing trading strategies
Learning ONNX for trading
MetaQuotes , 2023.03.30 17:46
4. (Deep) Machine Learned Model Deployment with ONNX
Discusses the development of a Microsoft open source machine learning library that has been published on GitHub.
The author explains the problem of deploying a machine learning model , where the model is built on a large machine with gigabytes of memory, but its usage conditions are very different and require optimization for one prediction at a time.
The author demonstrates the performance of various libraries such as scikit-learn, XGBoost and ML.NET and shows that the performance difference decreases as the package size increases. The author also presents ONNX as an optimization solution in such cases.
Learning ONNX for trading
Forum on trading, automated trading systems and testing trading strategies
Learning ONNX for trading
MetaQuotes , 2023.03.30 17:46
5. Recurrent Neural Networks | LSTM Price Movement Predictions For Trading Algorithms
The video discusses the use of recurrent neural networks, specifically LSTM networks, to predict price movements in financial markets such as FOREX, stocks, and cryptocurrencies.
The algorithm is written in Python and can be downloaded for experiments with changing the parameters of the algorithm.
Deep learning is known as an excellent predictive algorithm, here we test it in trading and price movement prediction. Technical indicators are also added, such as the RSI relative strength indicator and MA moving averages, to expand the inputs for the trading pattern.
Forum on trading, automated trading systems and testing trading strategies
Machine Learning and Neural Networks
MetaQuotes, 2023.04.07 10:38
1. The Deep Learning Revolution
This short video highlights the revolutionary role of artificial intelligence (AI) in achieving superhuman abilities, discovering new materials and conserving scarce resources.
These technologies allow visually impaired persons to recognize faces and to read text, as well as help blind children read. Self-driving vehicles give us the freedom to explore remote areas without street maps.
The video emphasizes the role of AI technology in strengthening people's ability to make better decisions and solve complex problems.
VGG16 Neural Network Visualization
Artificial Intelligence Full Course | Artificial Intelligence Tutorial for Beginners | Edureka
This Edureka video on "Artificial Intelligence" will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples.