Andrey Miguzov / Haber akışı
- Bilgiler
10+ yıl
deneyim
|
0
ürünler
|
0
demo sürümleri
|
1
işler
|
0
sinyaller
|
0
aboneler
|
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and ML (Part 29): Essential Tips for Selecting the Best Forex Data for AI Training Purposes](https://c.mql5.com/2/88/Data_Science_and_ML_Part_29___LOGO.png)
In this article, we dive deep into the crucial aspects of choosing the most relevant and high-quality Forex data to enhance the performance of AI models.
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and ML (Part 28): Predicting Multiple Futures for EURUSD, Using AI](https://c.mql5.com/2/87/Data_Science_and_ML_Part_28___LOGO.png)
It is a common practice for many Artificial Intelligence models to predict a single future value. However, in this article, we will delve into the powerful technique of using machine learning models to predict multiple future values. This approach, known as multistep forecasting, allows us to predict not only tomorrow's closing price but also the day after tomorrow's and beyond. By mastering multistep forecasting, traders and data scientists can gain deeper insights and make more informed decisions, significantly enhancing their predictive capabilities and strategic planning.
![Nikolai Semko - BeeXXI Corporation](https://c.mql5.com/avatar/2022/11/6383de4f-d007.jpg)
https://www.mql5.com/en/market/product/68043 - MT4
https://www.mql5.com/en/market/product/68039 - MT5
![](https://c.mql5.com/1/289/dpch1.gif)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and ML (Part 27): Convolutional Neural Networks (CNNs) in MetaTrader 5 Trading Bots — Are They Worth It?](https://c.mql5.com/2/84/Data_Science_and_ML_Part_27.png)
Convolutional Neural Networks (CNNs) are renowned for their prowess in detecting patterns in images and videos, with applications spanning diverse fields. In this article, we explore the potential of CNNs to identify valuable patterns in financial markets and generate effective trading signals for MetaTrader 5 trading bots. Let us discover how this deep machine learning technique can be leveraged for smarter trading decisions.
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and ML (Part 26): The Ultimate Battle in Time Series Forecasting — LSTM vs GRU Neural Networks](https://c.mql5.com/2/84/Data_Science_and_ML_Part_26__LOGO.png)
In the previous article, we discussed a simple RNN which despite its inability to understand long-term dependencies in the data, was able to make a profitable strategy. In this article, we are discussing both the Long-Short Term Memory(LSTM) and the Gated Recurrent Unit(GRU). These two were introduced to overcome the shortcomings of a simple RNN and to outsmart it.
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and Machine Learning (Part 25): Forex Timeseries Forecasting Using a Recurrent Neural Network (RNN)](https://c.mql5.com/2/82/Data_Science_and_ML_Part_25__LOGO.png)
Recurrent neural networks (RNNs) excel at leveraging past information to predict future events. Their remarkable predictive capabilities have been applied across various domains with great success. In this article, we will deploy RNN models to predict trends in the forex market, demonstrating their potential to enhance forecasting accuracy in forex trading.
![fxsaber](https://c.mql5.com/avatar/2019/8/5D67260D-44C9.png)
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and Machine Learning (Part 24): Forex Time series Forecasting Using Regular AI Models](https://c.mql5.com/2/81/Data_Science_and_Machine_Learning_Part_24__LOGO.png)
In the forex markets It is very challenging to predict the future trend without having an idea of the past, Very few machine learning models are capable of making the future predictions by considering past values. In this article, we are going to discuss how we can use classical(Non-time series) Artificial Intelligence models to beat the market
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and Machine Learning (Part 23): Why LightGBM and XGBoost outperform a lot of AI models?](https://c.mql5.com/2/79/Data_Science_and_ML_Part_23_____LOGO____2.png)
These advanced gradient-boosted decision tree techniques offer superior performance and flexibility, making them ideal for financial modeling and algorithmic trading. Learn how to leverage these tools to optimize your trading strategies, improve predictive accuracy, and gain a competitive edge in the financial markets.
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Nikolai Semko - BeeXXI Corporation](https://c.mql5.com/avatar/2022/11/6383de4f-d007.jpg)
Ultra-fast recognition of parabolic channels (as well as linear, horizontal and wavy channels) throughout the depth of history, creating a hierarchy of channels. Required setting: Max bars in chart: Unlimited This indicator is designed primarily for algorithmic trading, but can also be used for manual trading. This indicator will have a very active evolution in the near future and detailed descriptions on how to apply to create robots
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and Machine Learning (Part 22): Leveraging Autoencoders Neural Networks for Smarter Trades by Moving from Noise to Signal](https://c.mql5.com/2/77/Data_Science_and_ML_gPart_22k_____LOGO.png)
In the fast-paced world of financial markets, separating meaningful signals from the noise is crucial for successful trading. By employing sophisticated neural network architectures, autoencoders excel at uncovering hidden patterns within market data, transforming noisy input into actionable insights. In this article, we explore how autoencoders are revolutionizing trading practices, offering traders a powerful tool to enhance decision-making and gain a competitive edge in today's dynamic markets.