Intro to Retrieval Augmented Generation (RAG)
In this guide, we discuss a key concept for working with LLMs: retrieval augmented generation, or RAG.
By
Peter Foy
Academy
By
Peter Foy
Understanding Tokens & Context Windows
In this guide, we'll discuss two key concepts when working with LLMs: tokens & context windows.
By
Peter Foy
Understanding Transformers & the Architecture of LLMs
In this guide, we discuss the foundations of LLMs and the Transformer architecture.
By
Peter Foy
25+ Midjourney V6 Prompts
In this guide, we look at 25+ Midjourney V6 prompts and tips to get the most of the model.
By
Peter Foy
Getting Started with Midjourney V6
Midjourney V6 has arrived. In this guide, we explore the new in-image text capabilities & key updates.
By
Peter Foy
Text to Speech App with OpenAI & Streamlit
In this guide, we'll look at how to build a simple Streamlit app the converts text to speech with OpenAI's API.
By
Peter Foy
Getting Started with GPT-4 Vision for Data Analysis
In this guide, we look at how to get started with GPT-4 Vision for data analysis.
By
Peter Foy
Building an SEC Filings Assistant with GPT-4 Turbo
In this guide, we look at how to build an SEC filings assistant using GPT-4 Turbo and the Assistants API.
By
Peter Foy
Building an AI Financial Analyst with the Assistants API
In this guide, we discuss how to build an AI financial analyst using the Assistants API, function calling, and Code Interpreter.
By
Peter Foy
Parallel Function Calling for Financial Statements: Academy
In this video tutorial, we'll walk through how to get started with OpenAI's new parallel function calling capability for analyzing financial statements.
By
Peter Foy
Parallel Function Calling for Financial Statements
In this guide, we'll discuss how to use OpenAI's parallel function calling to answer investment research questions using financial statements.
By
Peter Foy
Getting Started with the Assistants API: Academy
In this video tutorial, we'll walk through how to get started with OpenAI's Assistants API.
By
Peter Foy
Getting Started with AutoGen: Academy
In this video tutorial, we'll walk through how to get started building AI agents with the open source framework: AutoGen.
By
Peter Foy
GPT 3.5 Fine Tuning for Structured Output: Academy
In this video tutorial, we'll discuss how use GPT 3.5 fine tuning for structured output formatting.
By
Peter Foy
GPT 3.5 Fine Tuning for Brand Tone of Voice: Academy
In this video tutorial, we'll discuss how use GPT 3.5 fine tuning to create a custom brand tone of voice.
By
Peter Foy
Getting Started with GPT 3.5 Fine Tuning: Academy
In this video, we'll walk through how to get started with GPT 3.5 fine tuning, including use cases & the step by step process to fine tune a model.
By
Peter Foy
Building a CSV Assistant with LangChain: Academy
In this video tutorial, we'll walk through how to use LangChain and OpenAI to create a CSV assistant that allows you to chat with and visualize data with natural language.
By
Peter Foy
GPT Function Calling: Building an AI Stock Screener
In this video tutorial, we'll walk through how to use GPT's new function calling capability to convert natural language into a stock screening API call.
By
Peter Foy
GPT-4 for Crypto On-Chain Analysis: Academy
In this video tutorial, we'll walk through how to use GPT-4 to summarize and analyze on-chain trading signals for crypto assets.
By
Peter Foy
GPT-4 for Financial Ratios: Academy
In this video tutorial, we'll walk through how to use GPT-4 to analyze financial ratios, including liquidity, profitability, valuation, and other key metrics.
By
Peter Foy
GPT-4 for Financial Statements: Academy
In this video tutorial, we'll walk through how to use GPT-4 to summarize and analyze financial statements, including income, balance sheet, and cash flow statements of public companies.
By
Peter Foy
AutoGPT & LangChain: Automated Research Assistant [Academy]
In this video tutorial, we'll walk through how to build an implementation of AutoGPT using LangChain.
By
Peter Foy
AutoGPT & LangChain: Building an Automated Research Assistant
In this guide, we'll walk through how to build an implementation of AutoGPT using LangChain and LLM primitives.
By
Peter Foy
Adding Long Term Memory to AutoGPT with Pinecone
In this guide, we'll look at how to add long term memory with Pinecone to AutoGPT, the experimental GPT-4 project taking the AI world by storm.
By
Peter Foy
Getting Started with AutoGPT: Academy
In this video tutorial, we'll walk through how to get started with AutoGPT: the autonomous GPT-4 experiment taking the AI world by storm.
By
Peter Foy
Getting Started with AutoGPT: an Autonomous GPT-4 Experiment
In this guide, we'll discuss how to get started with Auto-GPT, the autonomous GPT-4 experiment taking the AI world by storm.
By
Peter Foy
Prompt Engineering: Advanced Techniques
In this guide, we review several advanced prompt engineering techniques, including chain of shought (CoT) prompting, self consistency, ReAct, and more.
By
Peter Foy
Getting Started with Midjourney: A Beginners Guide
In this beginners guide to Midjourney, we discuss how to get started with the Midjourney Discord server, how to setup your own server, and prompt engineering best practices.
By
Peter Foy
GPT-4 & Streamlit - Building a Frontend for an AI/ML Tutor: Academy
In this video tutorial, we'll build a simple frontend for an AI/ML tutor using GPT-4, Streamlit, and Pinecone.
By
Peter Foy
GPT-4 & Pinecone - Ask Questions About Any Website: Academy
In this video tutorial, we're walk through a Colab notebook that shows you how to augment GPT-4 with a separate body of knowledge to create a custom AI assistant.
By
Peter Foy
GPT-4 & Pinecone: Turning a Website into an AI Assistant
In this guide, we're going to augment GPT-4 with a separate body of knowledge and use a vector database to create a custom AI assistant.
By
Peter Foy
Prompt Engineering: Improving Responses & Reliability
In this guide, we'll discuss several prompt engineering techniques and best practices to improve GPT-3 and GPT-4 responses and reliability.
By
Peter Foy
Introduction to Prompt Engineering: Key Concepts & Use Cases
In this guide, we'll discuss prompt engineering, which involves the skillful design or input prompts to large language models (LLMs) to improve their performance.
By
Peter Foy
Building an AI Research Assistant with LangChain & Pinecone: Academy
In this video tutorial, we'll discuss how you can use GPT-3, LangChain, and Pinecone to create an AI research assistant.
By
Peter Foy
Building a GPT-3 Enabled Document Assistant with LangChain: Academy
In this video tutorial, we'll discuss how to use LangChain and the OpenAI Embeddings in order to upload unstructured documents and be able to ask questions about the document using GPT-3
By
Peter Foy
Getting Started with LangChain: Academy
In this video tutorial, we'll walk through how to get started with a powerful library for building more advanced LLM-enabled applications: LangChain.
By
Peter Foy
Getting Started with LangChain
In this prompt engineering guide, we'll discuss how to get started with a powerful library for building more complex LLM applications: LangChain.
By
Peter Foy
Getting Started with the ChatGPT API: Academy
In this video tutorial we'll walk through how to get started with the ChatGPT API, including how to make your first API request, best practices, and more.
By
Peter Foy
Guide to Deep Reinforcement Learning: Key Concepts & Use Cases
This guide is discuss the application of neural networks to reinforcement learning. Deep reinforcement learning is at the cutting edge of AI.
By
Peter Foy
Deep Reinforcement Learning for Trading: Deploying the Algorithm at Interactive Brokers
In this section we'll finish our initial deep reinforcement learning trading algorithm by deploying it at a simulated account at Interactive Brokers.
By
Peter Foy
Deep Reinforcement Learning for Trading: Using Gradient Ascent to Maximize Sharpe Ratio
In this section, the objective is to use reinforcement learning to maximize the Sharpe ratio using gradient ascent.
By
Peter Foy
Deep Reinforcement Learning for Trading: Building a CNN for Probability
In this section, we're going to add another deep learning model to our trading algorithm and build a convolutional neural network (CNN).
By
Peter Foy
Deep Reinforcement Learning for Trading: Building an LSTM for Price Prediction
In this guide we build an LSTM for price prediction in our deep reinforcement learning trading algorithm.
By
Peter Foy
Deep Reinforcement Learning for Trading: Imports, Inputs, & Helper Functions
In this section we'll start with the imports, model and trading logic inputs, and helper functions that we'll need for this deep reinforcement learning for trading project.
By
Peter Foy
Deep Reinforcement Learning for Trading: Project Overview
In this project we're going to build a deep reinforcement learning trading agent and deploy it in a simulated trading account at Interactive Brokers.
By
Peter Foy
What is Reinforcement Learning? A Complete Guide for Beginners
In this article, we take a scientific look at how we learn through trial and error with a computational approach called reinforcement learning.
By
Peter Foy
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.
By
Peter Foy
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.
By
Peter Foy
Deep Reinforcement Learning: Guide to Deep Q-Learning
In this article, we discuss two important topics in reinforcement learning: Q-learning and deep Q-learning.
By
Peter Foy
Fundamentals of Reinforcement Learning: Dynamic Programming
Dynamic programming is fundamental to many reinforcement learning algorithms. In this article, we discuss how it can be used for policy evaluation and control.
By
Peter Foy