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**Language:** English

**Instructors:** Dr Jon Krohn

$150 92% OFF

## $12

Essential Linear Algebra and Calculus Hands-On in NumPy, TensorFlow, and PyTorch

**Join our "Bundle Data Science Course" to get more discount on complete Data Science & Machine Learning Courses**

Mathematics forms the core of data science and machine learning. Thus, to be the best data scientist you can be, you must have a working understanding of the most relevant math.

Getting started in data science is easy thanks to high-level libraries like Scikit-learn and Keras. But understanding the math behind the algorithms in these libraries opens an infinite number of possibilities up to you. From identifying modeling issues to inventing new and more powerful solutions, understanding the math behind it all can dramatically increase the impact you can make over the course of your career.

Led by deep learning guru Dr. Jon Krohn, this course provides a firm grasp of the mathematics — namely linear algebra and calculus — that underlies machine learning algorithms and data science models.

Course Sections

- Linear Algebra Data Structures
- Tensor Operations
- Matrix Properties
- Eigenvectors and Eigenvalues
- Matrix Operations for Machine Learning
- Limits
- Derivatives and Differentiation
- Automatic Differentiation
- Partial-Derivative Calculus
- Integral Calculus

Throughout each of the sections, you'll find plenty of hands-on assignments, Python code demos, and practical exercises to get your math game in top form!

This Mathematical Foundations of Machine Learning course is complete, but in the future, we intend on adding bonus content from related subjects beyond math, namely: probability, statistics, data structures, algorithms, and optimization. Enrollment now includes free, unlimited access to all of this future course content — over 25 hours in total.

Are you ready to become an outstanding data scientist? See you in the classroom.

Who this course is for:

You use high-level software libraries (e.g., scikit-learn, Keras, TensorFlow) to train or deploy machine learning algorithms, and would now like to understand the fundamentals underlying the abstractions, enabling you to expand your capabilities

You’re a software developer who would like to develop a firm foundation for the deployment of machine learning algorithms into production systems

You’re a data scientist who would like to reinforce your understanding of the subjects at the core of your professional discipline

You’re a data analyst or A.I. enthusiast who would like to become a data scientist or data/ML engineer, and so you’re keen to deeply understand the field you’re entering from the ground up (very wise of you!)

Requirements:

- All code demos will be in Python so experience with it or another object-oriented programming language would be helpful for following along with the hands-on examples.
- Familiarity with secondary school-level mathematics will make the class easier to follow along with. If you are comfortable dealing with quantitative information — such as understanding charts and rearranging simple equations — then you should be well-prepared to follow along with all of the mathematics.

After successful purchase, this item would be added to your courses.You can access your courses in the following ways :

- From the computer, you can access your courses after successful login
- For other devices, you can access your library using this web app through browser of your device.
- Soon Android & iOS app will be available.

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