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Automated trading with Python is an efficient way to analyze market data and make trading decisions. By using libraries like yfinance, Pandas, NumPy, and Matplotlib, traders can fetch historical stock data, calculate technical indicators such as Simple Moving Averages (SMA), and visualize stock trends. This method helps in creating a basic but effective trading strategy, where past stock prices and key calculations inform buying and selling decisions. Before deploying it in real trading, the strategy is tested using historical data to validate its effectiveness.The Python-based trading strategy focuses on analyzing price movements using SMA crossovers, where buy and sell signals are generated based on short-term and long-term trends. The approach simulates trades and calculates daily and cumulative returns to evaluate the performance of the strategy. Visualizing stock price movements, SMA lines, and cumulative returns allows traders to understand market behavior and assess the strategy's success in comparison to a buy-and-hold approach. This process helps build a foundation for automated trading systems that can work independently with minimal human intervention. For more details, please go through - <a href="https://www.geeksforgeeks.org/automated-trading-using-python/">Automated Trading using Python</a>

Automated Trading using Python

This video provides a comprehensive overview of the Support Vector Machine (SVM) algorithm, a powerful tool in machine learning. Gain a deep understanding of how SVM works, its principles, and its applications in classification and regression tasks.

Support Vector Regression Intuition

<h2>Generators in Python</h2>In this video, we will explore generators in Python. Generators provide a convenient way to implement iterators with a concise syntax, allowing you to create sequences of values on the fly. This tutorial is perfect for students, professionals, or anyone interested in enhancing their Python programming skills.<h3>Why Learn About Generators in Python?</h3>Understanding generators in Python helps to:<ul><li>Write more efficient and readable code.</li><li>Handle large datasets without consuming a lot of memory.</li><li>Improve your ability to work with sequences and iterative data processing.</li></ul><h3>Key Concepts</h3>1. Generators:<ul><li>Special types of iterators that allow you to iterate through a sequence of values. They are defined using functions and the yield statement.</li></ul>2. yield Statement:<ul><li>Unlike return, which exits a function and passes a value back to the caller, yield produces a value and suspends the function's state, allowing it to resume from where it left off.</li></ul>3. Memory Efficiency:<ul><li>Generators generate items one at a time and only when required, which is more memory-efficient than holding the entire sequence in memory.</li></ul><h3>Steps to Create and Use Generators in Python</h3>1. Define a Generator Function:<ul><li>Use the def keyword to define a function and use yield instead of return to generate values.</li></ul>2. Iterate Over Generator:<ul><li>Use a for loop or the next() function to retrieve values from the generator.</li></ul>3. Practical Applications:<ul><li>Use generators for processing large datasets, infinite sequences, and stream processing.</li></ul><h3>Practical Applications</h3>Large Datasets:<ul><li>Process large datasets efficiently without loading the entire dataset into memory.</li></ul>Infinite Sequences:<ul><li>Generate infinite sequences of values, such as numbers, where traditional lists would be impractical.</li></ul>Stream Processing:<ul><li>Handle real-time data streams effectively using generators.</li></ul><h2>Additional Resources</h2>For more detailed information and a comprehensive guide on generators in Python, check out the full article on GeeksforGeeks: <a href="https://www.geeksforgeeks.org/generators-in-python/">https://www.geeksforgeeks.org/generators-in-python/</a>. This article provides in-depth explanations, examples, and further readings to help you master this topic.By the end of this video, you’ll have a solid understanding of generators in Python, enhancing your ability to write efficient and readable code for iterative data processing.Read the full article for more details: <a href="https://www.geeksforgeeks.org/generators-in-python/">https://www.geeksforgeeks.org/generators-in-python/</a>.Thank you for watching!

Generators in Python

This Python Tkinter application demonstrates how to switch between multiple page frames. It creates three pages: StartPage, Page1, and Page2, each with buttons for navigation. The tkinterApp class initializes these frames and manages navigation using the show_frame function. Each page frame has buttons to switch between pages, making it ideal for multi-page GUI applications. This structure can be expanded for more complex projects with added features and functionality. For more details, check the full article <a href="https://www.geeksforgeeks.org/tkinter-application-to-switch-between-different-page-frames/">here</a>.

Tkinter Application to Switch Between Different Page Frames

In Python, an abstract class is a class that cannot be instantiated and serves as a blueprint for other classes. The abc module allows defining Abstract Base Classes (ABCs) and abstract methods that must be implemented by subclasses. Abstract methods are declared with the @abstractmethod decorator and do not contain an implementation. Subclasses are required to provide specific implementations for these abstract methods. This ensures consistency while allowing flexibility for specific behavior in subclasses. For more details, check the full article <a href="https://www.geeksforgeeks.org/abstract-classes-in-python/">here</a>.

Abstract Classes in Python

Implement a Movie Recommender System using Python and Pandas to suggest movies based on user preferences. Explore collaborative filtering, which analyzes user behavior and decisions, and content-based filtering, which recommends items based on discrete characteristics. This video provides steps to develop a basic recommendation system focusing on movie similarity. Download required files and learn to process a TSV file.&nbsp; For more detail information, read the full article <a href="https://www.geeksforgeeks.org/python-implementation-of-movie-recommender-system/">here</a>.

Python | Implementation of Movie Recommender System

Fine-tune the BERT model for sentiment analysis by adding custom neural layers while freezing pre-trained layers. This video covers loading datasets, tokenizing text, setting padding, and defining a classification architecture to classify sentences as positive or negative.&nbsp; For more detailed information, read the full article <a href="https://www.geeksforgeeks.org/fine-tuning-bert-model-for-sentiment-analysis/">here</a>.

Fine-tuning BERT model for Sentiment Analysis

The Disjoint Set data structure supports Find and Union operations for managing disjoint sets. The Find operation identifies the representative of a set, while the Union operation merges two sets by connecting their representatives. In the provided Python implementation, the find() method recursively traverses the parent array, and the unite() method links the roots of two sets. This implementation can lead to linear time complexity due to skewed tree structures. The worst-case scenario demonstrates how sets may become linked lists. For more details, visit the GeeksforGeeks article: <a href="https://origin.geeksforgeeks.org/introduction-to-disjoint-set-data-structure-or-union-find-algorithm/">Introduction to Disjoint Set (Union-Find Algorithm)</a>.

Find and Union Operation on Disjoint Sets

Given a list of characters, merge all of them into a string. Examples:Input : ['g', 'e', 'e', 'k', 's', 'f', 'o',&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 'r', 'g', 'e', 'e', 'k', 's'] Output : geeksforgeeksInput : ['p', 'r', 'o', 'g', 'r', 'a', 'm',&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;'m', 'i', 'n', 'g'] Output : programmingConvert a list of characters into a string in Python &nbsp;: <a href="https://www.geeksforgeeks.org/python-convert-list-characters-string/">https://www.geeksforgeeks.org/python-convert-list-characters-string/</a>

Convert a list of characters into a string in Python

Learn how to get the current timestamp in Python using different methods. The time module gives the timestamp as a floating-point number, while datetime.now() provides the current local time and its Unix timestamp. Using calendar.timegm(), you can convert structured time data into a Unix timestamp. These methods are essential for working with time-related tasks in Python applications. Explore each method to find the best fit for your needs. For more details, Visit the GeeksforGeeks article: <a href="https://www.geeksforgeeks.org/get-current-timestamp-using-python/">Get Current Timestamp Using Python</a>.

Get current timestamp using Python

Python's print() function by default ends with a newline, but the ‘end’ parameter allows customization of the output's ending character. You can print without a newline by setting the ‘end’ parameter to a space or any other character. Combining the 'end' and 'sep' parameters together enables more control over the formatting of the output. This is useful for tasks like concatenating strings or formatting CSV data in Python. Mastering the 'end' parameter can significantly improve output customization and formatting in Python. For more details, check out the full article: <a href="https://www.geeksforgeeks.org/gfact-50-python-end-parameter-in-print/">Python end parameter in print()</a>.

Python end parameter in print()

Python Tuple is a collection of Python objects, much like a list, that can store values of any type and are indexed by integers. Tuples are immutable and typically defined using parentheses, though tuple packing allows creating one without them. You can create tuples from strings, lists, or other sequences. Tuples support operations like indexing, unpacking, concatenation, and slicing, making them versatile for data manipulation. Python Tuples are essential for representing fixed collections and can be used as dictionary keys or set elements due to their immutability. For more details, check out the full article: <a href="https://www.geeksforgeeks.org/python-tuples/">Python Tuples</a>.