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Learner Reviews & Feedback for Calculus for Machine Learning and Data Science by DeepLearning.AI

4.8
stars
682 ratings

About the Course

Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises. As a learner in this program, you'll need basic to intermediate Python programming skills to be successful. After completing this course, learners will be able to: • Analytically optimize different types of functions commonly used in machine learning using properties of derivatives and gradients • Approximately optimize different types of functions commonly used in machine learning using first-order (gradient descent) and second-order (Newton’s method) iterative methods • Visually interpret differentiation of different types of functions commonly used in machine learning • Perform gradient descent in neural networks with different activation and cost functions Many machine learning engineers and data scientists need help with mathematics, and even experienced practitioners can feel held back by a lack of math skills. This Specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use easy-to-follow visualizations to help you see how the math behind machine learning actually works.  We recommend you have a high school level of mathematics (functions, basic algebra) and familiarity with programming (data structures, loops, functions, conditional statements, debugging). Assignments and labs are written in Python but the course introduces all the machine learning libraries you’ll use....

Top reviews

PB

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great course for an intro or refresher respecting optimization, regression, and classification

PK

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very very structured. Cant be more thankful to initiatives of Louis Serrano and Andrew NG, What a wonderful human service. Blessings from India

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101 - 125 of 146 Reviews for Calculus for Machine Learning and Data Science

By Kristaps F

Feb 23, 2024

Very useful

By Sabeur M

Jan 15, 2024

Great cours

By MARC F

Apr 18, 2023

So awesome!

By Pawel P

May 16, 2024

Thank you

By Jose M

Nov 15, 2023

Excelent!

By Renan d B L

Jul 19, 2024

Amazing!

By Abdul R W

Sep 21, 2023

done all

By emerson g

Aug 6, 2023

The Best

By Deepak K

Mar 29, 2023

good one

By Muhammad K I

Mar 26, 2024

awesome

By Trisno P R

Sep 25, 2023

jossss

By Alvin F P

Mar 24, 2024

great

By Anggi P S

Mar 23, 2024

good

By Nidula R

Jul 6, 2023

good

By Collins N

Aug 7, 2024

..

By Nurullah K

Jun 25, 2024

It was good untill week 3. My real point is 3.5 . I think this spec is definitely not a math course. they just show the math parts of the ML , they are just telling ML terms, this is a calculus course but subjects are what a neural network is, what a gradient descent is , or network method etc. Where exactly math here? There is no need if you dont tell it comrehensively , Every tutor is teaching much more math than this spec in any ML course. You are telling %10 percent math and then %90 percent ML terminology. Why do i have to learn what a neural network even with more than two layer in a math course. Then what are you gonna tell me in the ML course??? if you will, then make it like first two weeks. It was like equally math and ML but in week 3 it is %90 like an ML Course.

By Kevin W

Jul 10, 2024

Overall, it is an excellent introduction to calculus and applications to ML. However, some of the foundational explanations of differentiation need clarification. If you want a rigorous introduction to calculus, I recommend Khan's Academy. For example: in Khan's, you will find an in-depth explanation of limits which is only touched upon briefly in this course.

By Adison

Aug 13, 2023

Rather simple introduction to Calculus in machine learning & data science. The course covers core concepts and linked well to applications such as Optimisation and Gradient descent.

The instructor provided good graphical visualisations to help learners understand and develop intuition on the concepts covered.

By Aaron H

Oct 5, 2023

I actually understand gradient descent which is awesome. I need a little bit more practice running some of the problems to be proficient and remember how to do them, but I was able to complete them for the course and I suppose in real life I can just have my code (stolen from this course) find the answers.

By Mahbod I

Jun 19, 2023

An excellent course indeed, although with some caveats.

I love the simplicity and the examples of the instructor. However, sometimes the materials needed to be more complex and exciting to watch. I definitely recommend this course to absolute beginners in calculus or someone who needs a refresher.

By Yehan D

Aug 31, 2024

Content was extremely helpful but assignments were too simple. If you could make the graded content a little more challenging it might really help the student push himself further.

By Kavit S

May 23, 2023

We had a great time learning this course. We really had some good sessions with friends while learnin this. We found about new concepts. Thanks

By Amin N

Jun 15, 2023

Easy to follow for beginners. Concepts are well explained. I wish the Newtonian method had been explained in more details though.

By Susy

Sep 2, 2023

The last programming assignment has some problems. If you touch the optional part, you get 0.

By Axel D C

May 30, 2023

Knowledge very useful, however as benniger at phyton, programing task are quite hard