Name: Calculus for Machine Learning and Data Science
Brand: DeepLearning.AI
Availability: OnlineOnly
Rating: 4.8 (188 reviews)

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学生对 DeepLearning.AI 提供的 Calculus for Machine Learning and Data Science 的评价和反馈

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课程概述

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....

176 - Calculus for Machine Learning and Data Science 的 188 个评论（共 188 个）

创建者 AlAnoud B

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Nov 9, 2024

a little bit overwhelming. I still dont feel like I understand everything. I wish it was more interactive. especially with writing codes and mathematics. I was stuck with many questions and felt demotivated.

创建者 Arta A

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Dec 18, 2023

Useful for beginners and fundamental concepts. Before starting the course I thought that the course will be helpful in professional journey but I found out that the basic concepts are discussed.

创建者 Evgeny A

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Aug 3, 2023

Videos: great, easy to follow

Labs: not so great

创建者 Daniel K

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Apr 14, 2024

too easy

创建者 Partha R

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Feb 16, 2025

Some more details and maybe another week of new material would be good. Some of it was a rehash of the ML specialization coursera course. Explain also why integrals are not needed. didn't teach taylor series or other concepts that come up later in the probability course that are calculus related

创建者 andrew g

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Apr 12, 2024

Not possible without knowing Python 3 already. Went over easy topics too slowly and harder topics too quickly. Barely talking about ML so I'm still not sure how much of this relate.

创建者 Sachin K

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Aug 24, 2025

The course material and delivery felt confusing, disorienting at times. I'll have to look at other resources to better understand the topics.

创建者 Ehsan s

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May 26, 2024

better than linear algebra course.

创建者 Akshith R

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Mar 21, 2025

The linear algebra course was too good and this is exactly the opposite of it. I have no problem with the theory, the explanation was beautiful but when it comes to lab my first week graded lab file somehow got corrupted and it does not give me my grade. I'm disappointed with the graded labs; we cannot reset all the changes that we have made to square one again.

创建者 Omar A B

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Apr 30, 2023

the single start is definitely more than this course deserves, the specialization should be Titled Math for elementary school or for Kids. the explanation is soo naive and topics are not well covered! please Do NOT waste your TIME going through This course as the overall gain is almost ~0.000001

创建者 Michael S

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Nov 17, 2023

this is defenitly not helping beginners , topics are not covered in an easy way , labs are a complete nightmare , defenitly made me hate machine learning , not help me understand it