Turn Python Skills Into Cash: Stock Market Magic Revealed!
Download the source code from here:
https://onepagecode.substack.com/
00:00:00 Imports numpy, pandas, matplotlib, and io
00:01:38 Uploads and displays file details
00:02:41 Reads CSV file into a DataFrame
00:03:18 Display first 5 rows of dataframe
00:03:59 Prints number of rows and columns
00:04:23 Counts missing values in a dataframe
00:05:23 Plotting stock price over time
00:06:53 Convert, reshape, and store stock closing prices
00:07:39 Returns all elements in first column
00:08:31 Select and reshape stock closing values
00:09:32 Normalize stock data to a range
00:10:34 Split stocks data into training and testing
00:11:21 Prints variables 'train' and 'test'
00:12:02 Creates train dataset from stocks
00:12:54 Select stocks for testing
00:13:42 Reshapes arrays to have one column
00:14:07 Prints shapes of train and test datasets
00:14:51 Processes data for time series forecasting
00:16:17 Processes training and testing data
00:17:30 Prints shapes of training and testing data
00:18:07 Reshapes training and testing data arrays
00:18:45 Imports libraries for neural networks
00:20:07 Adjust learning rate and save best model
00:21:23 Defines a deep learning model architecture
00:23:40 Compiles a neural network model
00:24:42 Train a neural network model
00:26:02 Plot training and validation metrics
00:28:04 Evaluate model performance on training and testing data
00:29:09 Make predictions using scaled data
00:30:06 Reshapes, scales, and displays the first 10 elements
00:31:17 Plotting actual and predicted prices over time
00:32:17 Selects last 10 elements from testY
00:32:55 Selects elements of a list