# Math for Machine Learning

All knowledge is available on the web. All you need is a mentor to guide you to it.

"This track provides a refresher on continuous mathematics for Machine Learning students. The presentation, motivation, etc., are all from a machine learning perspective. The hope, however, is that itâ€™s useful in other contexts. The two major topics covered are linear algebra and calculus." Mohamed Elgendy

Hi, my name is Mohamed Elgendy. I'm the author of Grokking Deep Learning for Computer Vision book. I'm currently heading the engineering efforts at Synapse,  a leading AI company that builds proprietary computer vision applications to detect threats at security checkpoints worldwide.

What is this track about?

This track guides you through the main mathematics and statistics concepts that you need to understand to make sense of AI and Machine Learning applications.

By the end of this training you will:

• Understand the concept of Derivatives and how to calculate them
• Learn the different types of Regression Analysis and how they are used in ML
• Fit regression models using Least Squares and Gradient Descent
• Use Softmax and Sigmoid functions
• Identifying underfitting and overfitting by understanding the Bias-Variance tradeoff
• Learn Vectors and Matrices
• Calcular Eigen Values, Principal component analysis (PCA), and singular value decomposition (SVD)

This track is best suited for:

• Students with no Mathematics or Engineering background
• Professionals intending to study Machine Learning
• Data Scientists

#### Track at a glance

 Lessons 20 Commitment 4 hours Language English Mentor Response Time 5 hours Hrs. Student Reviews (145)

## Curriculum

• Video Lesson 2: What is a Derivative?
• Video Lesson 3: How to calculate Derivatives
• Video Lesson 5: Linear Regression
• Video Lesson 6: Multiple Linear Regression
• Video Lesson 8: Logistic Regression
• Video Lesson 9: Least Squares Method
• Video Lesson 11: How to choose the Learning Rate?
• Video Lesson 13: Softmax Regression & Sigmoid Function
• Video Lesson 14: Feature Scaling
• Video Lesson 15: Overfitting and Underfitting
• Video Lesson 16: Matrices and Vectors - WIP
• Video Lesson 18: Machine Learning Roadmap - WIP
• Readings/Downloads Lesson 19: Numpy, Pandas, Scikit, matplotlib, Tensorflow - WIP

## Learning at Mowgly

We believe that all knowledge is available on the web. All you need is a mentor to guide you to it. Tracks are not traditional online courses. A track is a series of videos, tasks and readings that are put together by industry experts to guide you to master your topic.

### Learn with Mentors

Mentors are here for you to guide you throughout your education journey. Enroll in a course and start chatting with your mentor instantly.

### Learn with others

Never get stuck. Whatever problem you have, someone in this world can fix it. Join our community of mentors and tech experts who are ready to share their expertise and provide career mentorship through our private chatting channel.

### Learn From Anywhere

Online educational courses that you can learn from your computer, tablet or phone to give you the flexibility to learn at your own pace.