Enroll Course: https://www.udemy.com/course/calculo-para-machine-learning-e-modelagem-com-python/
In the rapidly evolving world of Machine Learning and Artificial Intelligence, a strong foundation in mathematics is not just beneficial, it’s essential. For aspiring data scientists and ML engineers, understanding the underlying principles of calculus is paramount. This is where the Udemy course, ‘CÁLCULO PARA MACHINE LEARNING E MODELAGEM COM PYTHON’ (Calculus for Machine Learning and Modeling with Python), shines.
This comprehensive course offers a clear and objective approach to the core concepts of Differential and Integral Calculus, with a strong emphasis on practical demonstrations using Python. The curriculum covers a wide range of topics crucial for ML, including expressions, equations, functions, limits, derivatives (product rule, quotient rule, chain rule), successive derivatives, partial derivatives, gradients, gradient descent, regression models, indefinite integrals (substitution method, integration by parts), definite integrals, and applications of both derivatives and integrals.
What sets this course apart is its practical, Python-centric approach. You won’t just be learning theory; you’ll be implementing these concepts using Python, making the learning process more engaging and applicable to real-world ML tasks. The course also introduces other valuable mathematical software like Desmos, Geogebra, and Symbolab, providing a richer learning environment.
For those new to Python or Google Colaboratory, the course thoughtfully includes introductory sections on Python basics within Google Colaboratory. This ensures that learners with no prior experience can follow along comfortably. Furthermore, a dedicated section revisits the fundamental mathematical concepts necessary for a solid understanding of calculus, acting as a perfect refresher.
While the course is presented using Windows and Google Colaboratory, the content is easily accessible and adaptable for users on Linux and Mac. You can also utilize other Python IDEs such as Jupyter Notebook, Visual Studio, Pycharm, or Spyder.
The instructors are also receptive to feedback and suggestions for content additions, indicating a commitment to keeping the course dynamic and up-to-date. If you’re looking to bridge the gap between theoretical calculus and practical machine learning applications, this course is an excellent choice. It’s a fantastic entry point into the ‘fantastic world of Differential and Integral Calculus’ and a vital step towards mastering machine learning.
Enroll Course: https://www.udemy.com/course/calculo-para-machine-learning-e-modelagem-com-python/