Deep Learning: Recurrent Neural Networks in Python

GRU, LSTM, Time Series Forecasting, Stock Predictions, Natural Language Processing (NLP) using Artificial Intelligence

Created by: Lazy Programmer Inc.
Artificial intelligence and machine learning engineer

What Will I Learn?

• Apply RNNs to Time Series Forecasting (tackle the ubiquitous "Stock Prediction" problem)
• Apply RNNs to Natural Language Processing (NLP) and Text Classification (Spam Detection)
• Apply RNNs to Image Classification
• Understand the simple recurrent unit (Elman unit), GRU, and LSTM (long short-term memory unit)
• Write various recurrent networks in Tensorflow 2
• Understand how to mitigate the vanishing gradient problem
• Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion

Requirements

• Basic math (taking derivatives, matrix arithmetic, probability) is helpful
• Python, Numpy, Matplotlib

Target audience

• Students, professionals, and anyone else interested in Deep Learning, Time Series Forecasting, Sequence Data, or NLP
• Software Engineers and Data Scientists who want to level up their career