Comprehensive Guide to Financial Data Analysis and Prediction with Neural Networks in Python
Download the source code from here:
https://onepagecode.substack.com/
00:00:00 Imports libraries for data preprocessing
00:02:02 Reads, manipulates, and displays stock data
00:02:50 Reads and displays data from URL
00:03:50 Finds unique symbols in a DataFrame
00:04:45 Selects the first 11 elements
00:05:20 Select and drop symbol column for GOOG
00:06:19 Summarizes DataFrame information
00:06:56 Plot Google stock price analysis
00:08:11 Normalize stock data for plotting
00:09:38 Remove column, load stock data with windowing
00:10:58 Load training and testing data
00:11:59 Outputs shape of training data
00:12:28 It imports TensorFlow and Keras components
00:13:27 Creates a neural network model
00:14:32 Displays summary of model architecture
00:15:08 Compile model with MSE loss and SGD optimizer using 001 learning rate, Accuracy metric
00:15:39 Trains a model with data
00:16:48 Define neural network model and metrics
00:17:44 This code reshapes data for prediction
00:19:45 Reshapes the array to add dimension
00:20:52 Splits data into train and test
00:22:08 Creates and compiles a simple neural network
00:24:57 Fit a neural network model
00:27:02 Generate predictions using CNN model
00:28:00 Evaluate, plot and display model predictions