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Caltech's Machine Learning Course - CS 156. Lecture 18 - Epilogue
Forum on trading, automated trading systems and testing trading strategies
Machine Learning and Neural Networks
MetaQuotes, 2023.04.07 12:37
Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa
Caltech's Machine Learning Course - CS 156. Lecture 18 - Epilogue
In this final lecture of the course, the Professor Yaser Abu-Mostafa summarizes the diverse field of machine learning, covering theories, techniques, and paradigms. He discusses important models and methods such as linear models, neural networks, support vector machines, kernel methods, and Bayesian learning. The speaker explains the advantages and disadvantages of Bayesian learning, cautioning that prior assumptions must be valid or irrelevant for the approach to be valuable. He also discusses aggregation methods, including "after the fact" and "before the fact" aggregation, and specifically covers the AdaBoost algorithm. Finally, the speaker acknowledges those who have contributed to the course and encourages his students to continue learning and exploring the diverse field of machine learning.
The second part discusses the potential benefits of negative weights in a machine learning algorithm's solution and shares a practical problem he faced in measuring the value of a hypothesis in a competition. He also expresses gratitude towards his colleagues and the course staff, particularly Carlos Gonzalez, and acknowledges the supporters who made the course possible and free for anyone to take. Abu-Mostafa dedicates the course to his best friend and hopes that it has been a valuable learning experience for all participants.
Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 11:56
Trading with Python. Introduction & Setup
Introduction & Setup | Trading with Python
Trading with Python series is introduced in this video, which covers the basics of setting up Python and opening a trading account with a broker. The tutorial walks through the process of downloading Python and MT5 IDE, installing the MetaTrader5 library, and creating a Python script to open a trade. The speaker explains using IOC and GTC methods for filling orders and demonstrates how the script sends the order to the MT5 server. The video ends with a successful order execution and an invitation to subscribe to the channel.
Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 11:56
Trading with Python. Jupyter Notebook & Market Data
Jupyter Notebook & Market Data | Trading with Python #1
The "Jupyter Notebook & Market Data | Trading with Python #1" video introduces viewers to Jupyter Notebook and market data. Jupyter Notebook is a popular web-based coding environment used for data visualization and analysis, strategy development, and backtesting. Viewers can access market data such as tech data and OHLC data by extracting trail symbols from Metatrader 5 and requesting market data. The narrator demonstrates how to obtain bid and ask prices with Python using the datetime library and how to request data periodically via a while loop using the time module, resulting in real-time updates.
Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 11:57
Trading with Python. Connect Python to MetaTrader5
Connect Python to MetaTrader5
The video tutorial demonstrates how to integrate Python with the MetaTrader5 platform, including importing necessary libraries such as pandas and plotly, initializing and logging into a trading account, retrieving account information, and getting data for symbols, including current price, OHLC data, and historical ticks and transactions. The tutorial also covers how to interact with the platform through Python to view orders, send trades to open and close positions, and close positions using ticket IDs. The presenter encourages viewers to ask questions about the integration process.
Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 11:58
Trading with Python. Code a simple Trading Robot
Code a simple Trading Robot | Trading with Python
The video tutorial demonstrates how to code a simple trading robot in Python using the MetaTrader 5 platform. The robot uses a simple moving average crossover strategy, with buying occurring when a candle closes above the moving average and selling when the candle closes below it. The presenter explains the code written in Python for this strategy, including functions for market orders, closing orders, and getting exposure for specific symbols. The signal function generates trading signals based on the strategy, and the robot settings define the parameters for the symbol, volume, time frame, and deviation. The video also covers the logic of the trading strategy and code needed to implement it, with buy and sell signals leading to buy or sell orders, respectively. Viewers are encouraged to suggest trading ideas or strategies for potential video topics.
Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 11:59
Trading with Python. How to send Orders to the Market
How to send Orders to the Market | Trading with Python #3
In this video tutorial, the presenter demonstrates how to send market orders using Python and MetaTrader 5. The tutorial covers creating a request dictionary with parameters for a market order, including trade action, symbol, volume, and order type, as well as additional parameters such as stop loss, take profit, deviation, and comment. The video also covers closing open positions using the positions get method and passing the ticket number of the order. The tutorial then moves on to opening a limit or stop order with specifications for price, volume, and other parameters, and modifying and deleting orders using the mt5.trade action stop loss take profit and mt5.trade action remove commands, respectively.
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Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 12:01
Trading with Python. How to close ALL positions
How to close ALL positions | Trading with Python #4
The video tutorial demonstrates how to use Python to close all positions in the MetaTrader 5 trading platform. This entails importing the MetaTrader5 library and using the mt5.positions.get method to retrieve the current list of open positions. A 'close_position' function is then defined, utilizing the mt5.symbol_info_tick method to get the current price and a request dictionary to communicate with the trading platform. The program loops through the open position list, passing each position to the 'close_position' function to close every trade. The narrator provides a link to the code and tutorial playlist for further Python training.
Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 12:02
Trading with Python. Extract and Visualize Data
Extract and Visualize Data | Trading with Python #5
The video demonstrates how to extract and visualize daily OHLC data for the EURUSD symbol from MetaTrader 5 using Python. The process involves importing libraries like MetaTrader 5, pandas, and Plotly.graph_objects for data visualization. The extracted data is converted into a Pandas dataframe and visualized using Plotly's OHLC function. The presenter also shows how to hide the range slider on the plot and provides links to download the code and more Trading with Python videos.
Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 12:04
Trading with Python. Code a Trailing Stoploss
Code a Trailing Stoploss | Trading with Python #6
The video showcases how to create a trailing stop loss robot, utilizing Python. The presenter explains how a trailing stop loss can benefit traders by limiting losses and maximizing profits. The video covers the configuration of necessary variables and connections to the drive platform, in addition to retrieving data and defining maximum distances between the current price and stop loss. The presenter also demonstrates how the stop-loss function follows profit, updates to break even in the event of a breakout, and is capable of updating based on the current price. Overall, the video serves as a helpful demonstration of how Python can be used to trail positions.
Forum on trading, automated trading systems and testing trading strategies
Python in algorithmic trading
MetaQuotes, 2023.04.13 12:05
Trading with Python. Manage your positions with Tkinter
Manage your positions with Tkinter | Trading with Python #7
In this section of the video, the presenter demonstrates how to use Tkinter to create a Python application that can manage and close open positions remotely in the MetaTrader 5 platform. The application allows users to monitor real-time updates and close positions with deviations in place to limit slippage. It uses a list box to display open positions and has a close button that is linked to a close position command with a deviation element defined using a label and entry. The code for the application is available for free download on the presenter's website, and the video provides a step-by-step explanation of how to create the GUI, initialize the MetaTrader 5 platform, and use functions to monitor and close positions.