CALCULUS for DATA SCIENCE & MACHINE LEARNING COURSE DESCRIPTION

• What is Calculus?

• Applications of Calculus in ML

• Calculus Notation

• Computation Map

• Linear Functions

• Derivative

• Product & Quotient Rule

• Exponential & Logarithm Rule

• Sine and Cosine Functions

• Sigmoid Function

• Hyperbolic Function

• Chain Rule

• Differentiation

• Multivariable Functions

• Partial Differentiation

• Sigma Notation

• Taylor/Mclaurin Series Expansion

• Integration

• Area Between Curves

• Distance Measurement

• Argmax – Argmin

WHY CALCULUS?

• Calculus is absolutely key to understanding the linear algebra and statistics you need in machine learning and data science.

• If you can understand machine learning methods at the level of derivative you will improve your intuition for how and when they work.

• A deeper understanding of the algorithm and its constraints will allow you to customize its application and better understand the impact of tuning parameters on the results.

THE OPPORTUNITIES YOU WILL HAVE WITH THIS COURSE

• In-class support: We don't just give you video lessons. We have created a professional Python Programmer team and community to support you. This means that you will get answers to your questions within 24 hours.

WHO WE ARE: DATAI TEAM ACADEMY

DATAI TEAM is a team of Python Programmers and Data Scientists.

Let's register for the course and start to Calculus for Data Science & Machine Learning.