Learn to forecast mathematical number sequences using machine learning regression techniques in this hands-on video tutorial. Generate number series with various mathematical functions including quadratic equations, exponentials, logarithmic, and trigonometric functions using Python, pandas, and numpy. Apply scikit-learn regression models to predict future numbers based on the source sequences. Visualize data and validate forecasts using matplotlib. Cover topics such as adding noise to sequences, comparing uniform and exponential distributions, and implementing linear regression for different mathematical functions. Gain practical experience in sequence generation, model training, and forecasting for functions like sin(x) and cos(x). Perfect for those looking to enhance their skills in mathematical modeling and machine learning applications.