Free Maths for Machine Learning Course
Free Mathematics for Machine Learning Online Certification Course
About this Free Maths for Machine Learning Course
Welcome to our "Free Mathematics for Machine Learning Online This free Mathematics for Machine Learning course is designed to provide an essential foundation in the key mathematical concepts used in ML algorithms. It covers linear algebra, calculus, and probability, allowing learners to understand and implement machine learning models effectively. The course is suitable for beginners and seasoned professionals.
What you’ll learn
- Understanding Core Mathematical Concepts: You'll gain a firm grasp of the fundamental mathematical concepts underpinning machine learning, including linear algebra, calculus, probability, and statistics.
- Application of Mathematical Concepts: This course will teach you how to apply these mathematical principles to solve real-world problems, enhancing your problem-solving skills.
- Proficiency in Mathematical Tools: You will gain hands-on experience using various tools and software for mathematical computation, thus translating theory into practical application.
- Mathematical Foundation for Machine Learning: You'll understand how these mathematical concepts apply specifically to machine learning, forming a robust foundation for further study and application in the field.
Course Content
Certificate for Free Maths for Machine Learning Course
Instructor of this course
- Co-Founder & Principal Instructor, Applied AI & AppliedRoots
- Senior ML Scientist @ Amazon, Palo Alto and Bangalore
- Co-Founder, Matherix Labs
- Research Engineer, Yahoo! Labs
- Masters from IISc Bangalore, Gate 2007(AIR 2)
- 13 years of experience in AI and Machine Learning
Pre-requisites for free maths for machine learning certification course
-
Basic Mathematical Knowledge: A foundational understanding of mathematics, particularly in areas like algebra and basic calculus, is advantageous as these concepts will be expanded upon in the course.
-
Basic Programming Skills: Since mathematical concepts are often implemented in code, a basic understanding of any programming language, preferably Python, will be beneficial.
-
Familiarity with Basic Machine Learning Concepts: While not necessary, having a general understanding of machine learning can provide helpful context for how the mathematical concepts taught in the course are used in practice.
-
Willingness to Learn: A strong desire to learn new concepts and willingness to put in the necessary time and effort is the most crucial prerequisite for this course.
Who should learn this free PyTorch deep learning course?
-
Aspiring Data Scientists and AI Specialists: Individuals looking to break into the field of data science, AI, or machine learning would greatly benefit from learning PyTorch, a leading deep learning framework.
-
Software Engineers: Software engineers interested in broadening their skillset to include deep learning techniques can gain significant value from this course.
-
Existing Machine Learning Practitioners: For those already working with other deep learning frameworks like TensorFlow, learning PyTorch can open up a wider range of tools and options for model development and research.
-
Researchers and Academics: Professionals and scholars in fields like computer science, cognitive neuroscience, and artificial intelligence can learn PyTorch to conduct cutting-edge research in deep learning and neural networks.