An Introduction to Recurrent Neural Networks & LSTMs
A recurrent neural network (RNN) attempts to model time-based or sequence-based data. An LSTM network is a type of RNN that uses special units as well as standard units.
Naive Bayes for Sentiment Analysis & Natural Language Processing (NLP)
In this article on natural language processing, we discuss how to use the Naive Bayes formula for the purpose of sentiment analysis.
Deep Reinforcement Learning for Trading: Strategy Development & AutoML
In this guide, we discuss the application of deep reinforcement learning to the field of algorithmic trading.
Natural Language Processing (NLP) for Sentiment Analysis with Logistic Regression
In this article, we discuss how to use natural language processing and logistic regression for the purpose of sentiment analysis.
Deep Reinforcement Learning for Trading with TensorFlow 2.0
In this article we look at how to build a reinforcement learning trading agent with deep Q-learning using TensorFlow 2.0.
Introduction to Markowitz Portfolio Optimization and the Efficient Frontier
In this article, we discuss two key concepts in portfolio optimization: Markovitz optimization and the Efficient Frontier.
Introduction to Portfolio Construction and Analysis: Risk & Returns
In this article, we'll introduce key concepts of risk and return in portfolio analysis, including Value-at-Risk, Conditional Value-at-Risk, and more.
Deep Reinforcement Learning: Guide to Deep Q-Learning
In this article we cover an important topic in reinforcement learning: Q-learning and deep Q-learning.