Course Information
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Course Overview
Master Calculus: Essential Math for AI, Deep Learning, Machine Learning, Data Science, Data Analysis, and AI - Hands-On
Unlock the Power of Calculus in Machine Learning, Deep Learning, Data Science, and AI with Python: A Comprehensive Guide to Mastering Essential Mathematical Skills"
Are you striving to elevate your status as a proficient data scientist? Do you seek a distinctive edge in a competitive landscape? If you're keen on enhancing your expertise in Machine Learning and Deep Learning by proficiently applying mathematical skills, this course is tailor-made for you.
Calculus for Deep Learning: Mastering Calculus for Machine Learning, Deep Learning, Data Science, Data Analysis, and AI using Python
Embark on a transformative learning journey that commences with the fundamentals, guiding you through the intricacies of functions and their applications in data fitting. Gain a comprehensive understanding of the core principles underpinning Machine Learning, Deep Learning, Artificial Intelligence, and Data Science applications.
Upon mastering the concepts presented in this course, you'll gain invaluable intuition that demystifies the inner workings of algorithms. Whether you're crafting self-driving cars, developing recommendation engines for platforms like Netflix, or fitting practice data to a function, the essence remains the same.
Key Learning Objectives:
Function Fundamentals: Initiate your learning journey by grasping the fundamental definitions of functions, establishing a solid foundation for subsequent topics.
Data Fitting Techniques: Progress through the course, delving into data fitting techniques essential for Machine Learning, Deep Learning, Artificial Intelligence, and Data Science applications.
Approximation Concepts: Explore important concepts related to approximation, a cornerstone for developing robust models in Machine Learning, Deep Learning, Artificial Intelligence, and Data Science.
Neural Network Training: Leverage your acquired knowledge in the final sections of the course to train Neural Networks, gaining hands-on experience with Linear Regression models by coding from scratch.
Why Enroll in This Course?
Comprehensive Learning: From fundamental function understanding to advanced concepts of approximation, the course covers a spectrum of topics for a well-rounded understanding of Calculus in the context of Data Science.
Practical Application: Translate theoretical knowledge into practical skills by coding Neural Networks and Linear Regression models using Python.
Premium Learning Experience: Developed by experts with valuable feedback from students, this course ensures a premium learning experience that aligns with industry demands.
Join now to build confidence in the mathematical aspects of Machine Learning, Deep Learning, Artificial Intelligence, and Data Science, setting yourself on a trajectory of continuous career growth. See you in Lesson 1!
Course Content
- 17 section(s)
- 115 lecture(s)
- Section 1 Basics of Calculus
- Section 2 Multi Variate Calculus
- Section 3 Chain Rule on Multi-Variate Functions
- Section 4 Taylor Series of Approximations
- Section 5 Neural Networks
- Section 6 Optimization Methods - Newton Raphson & Gradient Descent
- Section 7 Linear Regression
- Section 8 Calculus for Deep Learning
- Section 9 Working with Tensorflow
- Section 10 Finding the Derivative using Tensorflow - AutoGrad
- Section 11 Linear Regression with Deep learning
- Section 12 Linear Regression using Keras
- Section 13 Deep learning Tasks
- Section 14 Solution for Exercise
- Section 15 Python for Data Science - Refresh the Basics
- Section 16 Python for Data Science
- Section 17 Machine Learning for Projects
What You’ll Learn
- Build Mathematical intuition especially Calculus required for Deep learning, Data Science and Machine Learning
- The Calculus intuition required to become a Data Scientist / Machine Learning / Deep learning Practitioner
- How to take their Data Science / Machine Learning / Deep learning career to the next level
- Hacks, tips & tricks for their Data Science / Machine Learning / Deep learning career
- Implement Machine Learning / Deep learning Algorithms better
- Learn core concept to Implement in Machine Learning / Deep learning
Skills covered in this course
Reviews
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SStephen David C M
Absolutely usefull content. worth everyminute !
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KKonstantinos Ntetsikas
Good introduction into machine learning and model deployment methods
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MMamta Kumari .
Course content was really good. But the organization of overall course can be improved further. It was worth spending time on such type of course. Thanks :)
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GGarima Singh Bhadauria .
The approach and intuition helped the alot in better grasping the topics. Thanks.