Deep Learning and Machine Learning for trading and investment 🤖 🦾 🧠
Summary:
This is a comprehensive study and analysis of stocks using deep learning (DL) and machine learning (ML) techniques. Both machine learning and deep learning are types of artificial intelligence (AI). The objective is to predict stock behavior by employing various machine learning and deep learning algorithms. The focus is on experimenting with stock data to understand how and why certain methods are effective, as well as identifying reasons for their potential limitations. Different stock strategies are explored within the context of machine learning and deep learning. Technical Analysis and Fundamental Analysis are utilized to predict future stock prices using these AI techniques, encompassing both long-term and short-term predictions.
Machine learning is a branch of artificial intelligence that involves the development of algorithms capable of automatically adapting and generating outputs by processing structured data. On the other hand, deep learning is a subset of machine learning that employs similar algorithms but with additional layers of complexity, enabling different interpretations of the data. The network of algorithms used in deep learning is known as artificial neural networks, which mimic the interconnectedness of neural pathways in the human brain.
Deep learning and machine learning are powerful approaches that have revolutionized the AI landscape. Understanding the fundamentals of these techniques and the commonly used algorithms is essential for aspiring data scientists and AI enthusiasts. Regression, as a fundamental concept in predictive modeling, plays a crucial role in analyzing and predicting continuous variables. By harnessing the capabilities of these algorithms and techniques, we can unlock incredible potential in various domains, leading to advancements and improvements in numerous industries.
