Description
Mathematical Foundations of Machine Learning is an arithmetic and linear algebra course with a focus on data science and machine learning, published by Udemy Academy. Mathematics and its sub-disciplines such as algebra and calculus are in fact the heart and foundation of new knowledge such as artificial intelligence, data construction science and machine and deep learning and play a very important role in the implementation of systems based on these sciences. he does. Learning the basics of math can help you better understand machine learning problems and pave the way for your future career. With high-level libraries and frameworks such as Scikit-learn and Keras, people of all levels of knowledge can enter the world of science. But that doesn’t mean they specialize in those areas.
In order to deeply understand the logic behind the different algorithms and behind the scenes, the math-based systems of machine learning will play a very important role and open a window of infinity for you. One of the most important benefits of mastering math is identifying bugs in the process of modeling and developing more efficient and leaner algorithms. During the course training process and after each section, you will come across a series of focused exercises, sample Python application codes, and tests, which play a very important role in developing your skills.
What you will learn in the mathematical foundations of machine learning
- Knowledge of the basics of linear algebra and differential calculus
- Work with Python-based libraries NumPy, TensorFlow and PyTorch
- Implement the calculations and operations and vector matrices needed for machine learning and data science
- Reduce the multidimensionality of complex data and reduce it to essential data and elements with specific values and specific vectors, the method of Single Value Analysis or SVD and Principal Component Analysis or PCA
- Solve unknown and undefined variables using simple and advanced techniques
- Understand advanced differentiation rules such as the chain rule
- Deep understanding of machine learning algorithms
Course specifications
Publisher: Udemy
Instructors: Dr. Jon Krohn and The Ligency I team
French language
Level: Introductory to Advanced
Number of lessons: 105
Duration: 15 hours and 33 minutes
Course topics on 2021/11
Mathematical Foundations of Machine Learning
All code demonstrations will be in Python, so experience with this or another object-oriented programming language would be helpful to follow the hands-on examples.
The knowledge of mathematics at the secondary level will facilitate the follow-up of the class. If you are comfortable with quantitative information, such as understanding graphs and rearranging simple equations, you should be well prepared to take all the math.
Pictures
Introductory video to the mathematical foundations of machine learning
Installation guide
After ripping, watch with your favorite player.
english subtitle
Quality: 720p
Download links
File password(s): ngaur.com
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3.96 GB