Mathematical Foundations for Deep LearningIntroduction to Probability and Statistics for Machine Learning

Probability and statistics form the foundation for understanding data and making informed decisions in machine learning. This course will focus on key concepts and techniques that hold significant importance in the realm of deep learning.

Probability of Rolling a 2 on a Die

Probability of Rolling 6 on Two Dice

Calculating Probability of Rolling a 6 or 5 on a Dice

Rolling a 6 on One Die and Not a 6 on the Other Die

Calculate Probability of Even or Divisible by Six Rolls

Conditional Probability of Drawing a Heart Given an Ace

Calculate Average Monthly Temperature and Standard Deviation

Calculating Mean and Standard Deviation for Monthly Sales Data

Calculate the Median of Salaries

Increase the Standard Deviation of a Dataset

Analyzing Drug Effectiveness with Descriptive Statistics

Comparing Mean Temperatures of Two Cities

Adjust and Plot PDFs with Different Standard Deviations

Adjusting Mean Values and Plotting PDF

Generate and Visualize Uniform Distribution Sample

Plotting PDF and CDF of Exponential Distribution

Plotting and Analyzing the CDF of a Normal Distribution

Plotting the CDF of Uniform Distribution for Sunlight Hours

Hypothesis Testing for Exam Scores

Perform a One-Sample T-Test on Daily Water Intake

Two Sample T-Test for Teaching Methods

Best-Fit Line for House Prices

Predict Saucer Sightings for Future Months

Best-Fit Line for Temperature and Ice Cream Sales

Predict House Prices Using Linear Regression