Name: Probability & Statistics for Machine Learning & Data Science
Brand: DeepLearning.AI
Availability: OnlineOnly
Rating: 4.6 (122 reviews)

返回到 Probability & Statistics for Machine Learning & Data Science

学生对 DeepLearning.AI 提供的 Probability & Statistics for Machine Learning & Data Science 的评价和反馈

4.6

星

598 个评分

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, you will be able to: • Describe and quantify the uncertainty inherent in predictions made by machine learning models, using the concepts of probability, random variables, and probability distributions. • Visually and intuitively understand the properties of commonly used probability distributions in machine learning and data science like Bernoulli, Binomial, and Gaussian distributions • Apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems • Assess the performance of machine learning models using interval estimates and margin of errors • Apply concepts of statistical hypothesis testing to commonly used tests in data science like AB testing • Perform Exploratory Data Analysis on a dataset to find, validate, and quantify patterns. 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....

101 - Probability & Statistics for Machine Learning & Data Science 的 125 个评论（共 126 个）

创建者 Nanda P N N

•

Mar 22, 2024

COOLLLL

创建者 Dwiki H

•

Sep 29, 2023

so cool

创建者 KURRA V T

•

Jan 21, 2025

SUPERB

创建者 Ni K P S

•

Sep 27, 2023

Great!

创建者 Nguyen N H L

•

Aug 20, 2025

great

创建者 Daniel K

•

Apr 14, 2024

great

创建者 Thansheeh K T

•

Mar 21, 2025

good

创建者 Sandesh L

•

Mar 6, 2025

Best

创建者 KURELLA R

•

Sep 17, 2024

GOOD

创建者 syabiroe

•

Nov 30, 2023

nice

创建者 Alif W S

•

Oct 2, 2023

Good

创建者 Adek P D

•

Sep 29, 2023

nice

创建者 TAMPAN S

•

Oct 10, 2023

创建者 Diego E M S

•

Feb 14, 2025

I really enjoy this course, lern a lot of things, the content is very helpful and the quality of the video is good and the novel here, are the of the professor's examples to illustrate the concepts, however I would like to do a critic review about this course, I have would like to go deep in some concepts or prerequisites like t-student distribution, central limit theorem, law of large numbers , beta distribution and dirichelt distribution, I consider very important concept for the course thanks you very much, Profe Luis Serrano

创建者 ADITYA V S

•

Aug 6, 2024

Indepth and apt knwoledge about probability and statistics and their use-case in real life situations such as using confidence intervals which help you to understand the variablility, precision and reliability of your estimates. Also it has hypothesis testing that allows to verify your hypothesis based on data. Overall a very good course.

创建者 Ericy

•

Jun 17, 2024

Very thorough and easy to comprehend approach to learning statistical and probability theory which is important foundational knowledge, not just in ML but any field of data analytics!

创建者 Anshul Y

•

Jul 1, 2024

I think graded quiz was good, but the programming assignments could be made more challenging to have a good understanding of python and math simultaneously.

创建者 Hadar D S (

•

Jul 5, 2024

This is definitely the hardest course in this specialization. It's definitely interesting and will help me a lot at school.

创建者 Salvador M

•

Sep 1, 2025

This course is basically good, but it should be added some difficult topic, such as SVD in Linear Algebra,...

创建者 Makoto T

•

Mar 29, 2025

I will recommend this course for everyone who want to have comprehensive and holistic view on data sciense.

创建者 Evert J K

•

Nov 12, 2024

Good course and gives a good understanding!

创建者 Nenda M K M

•

Oct 8, 2024

good course

创建者 Sufi A Q Z S Q A

•

Jul 20, 2025

good

创建者 Beyers S

•

Jan 22, 2024

Cannot finish this course, as my Python skills are lacking - yet, the course was advertised as for "beginners". I tried to submit my first programming assignment about 30 times, no success. Very disappointed.