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Learner Reviews & Feedback for The Nuts and Bolts of Machine Learning by Google

4.8
stars
410 ratings

About the Course

This is the sixth of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn about machine learning, which uses algorithms and statistics to teach computer systems to discover patterns in data. Data professionals use machine learning to help analyze large amounts of data, solve complex problems, and make accurate predictions. You’ll focus on the two main types of machine learning: supervised and unsupervised. You'll learn how to apply different machine learning models to business problems and become familiar with specific models such as Naive Bayes, decision tree, random forest, and more. Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. By the end of this course, you will: -Apply feature engineering techniques using Python -Construct a Naive Bayes model -Describe how unsupervised learning differs from supervised learning -Code a K-means algorithm in Python -Evaluate and optimize the results of K-means model -Explore decision tree models, how they work, and their advantages over other types of supervised machine learning -Characterize bagging in machine learning, specifically for random forest models -Distinguish boosting in machine learning, specifically for XGBoost models -Explain tuning model parameters and how they affect performance and evaluation metrics...

Top reviews

MB

Jul 24, 2023

A great course for anyone who wants to dive into the world of Machine Learning. The steps are easy to follow and the lectures and lengthy enough to give a complete idea of the topic.

DV

Jun 16, 2023

Really nice course that I came across The Nuts and Bolts of Machine Learning, I learnt a lot. Gained Advanced concepts like Hyper parameter tuning. Nicely curated course.

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51 - 61 of 61 Reviews for The Nuts and Bolts of Machine Learning

By parvati B

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Nov 7, 2024

Great

By vrushabh G

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Sep 3, 2024

great

By Wassim R

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Mar 28, 2024

great

By Harsh C

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Aug 24, 2024

n nm

By Inam U

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Aug 10, 2024

good

By Huy D V

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Apr 4, 2024

nice

By Zeng Y

•

Aug 8, 2023

.

By Evgeniy K

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Nov 20, 2024

Being an experienced programmer with math background but with rather outdated knowledge of ML, in order to refresh and expand my knowledge, I decided to take a series of ML courses from Andrew Ng, and then "The Nuts and Bolts..." (TN&B). TN&B pleasantly surprised me with an abundance of theory combined with a developer's perspective. Some topics, especially K-means, in my opinion, are explained even better than in the course from Andrew Ng. The labs and activities in Python seemed interesting to me at first, but by the end they were reduced to the monotonous creation of Tree Forests or XGBs. The final project was quite boring and, frankly, by the end I could not stand it and wrote part of the code using lots of copy-paste techniques. It seems to me that the authors of the course should have paid more attention to the issues of analyzing various scores and confusion matrices, since these are rather sophisticated topics. Based on the results, I can say that after the course there is practically no chance of becoming an ML programmer or getting a corresponding job if you were counting only on this course or specialization. But if you already have programming experience and some basic knowledge of ML, then the course is well suited to update your knowledge and get the big picture.

By RM T

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Jun 19, 2024

Good To Boost our skills

By pitipark J

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Jul 2, 2023

THE QUIZ IS SO HARD

By Aditya K

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Aug 26, 2024

very interesting