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Avis et commentaires pour d'étudiants pour Launching into Machine Learning par Google Cloud

4.6
étoiles
3,745 évaluations
433 avis

À propos du cours

Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of data science problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent. This involves creating datasets that permit generalization; we talk about methods of doing so in a repeatable way that supports experimentation. Course Objectives: Identify why deep learning is currently popular Optimize and evaluate models using loss functions and performance metrics Mitigate common problems that arise in machine learning Create repeatable and scalable training, evaluation, and test datasets...

Meilleurs avis

OD

May 31, 2020

Amazing course. For a beginner like me, it was a shot in the arm. Excellent presentation very lively and engaging. Hope to see the instructor soon in a another course. Thanks so much. I learned a lot.

PT

Dec 02, 2018

This is an awesome module. It will open up so much inside story of ML process which is core of the topic with such a simplicity. It greatly increases my interest into this topic and this course :)

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401 - 425 sur 431 Avis pour Launching into Machine Learning

par Manuele I

Apr 29, 2020

Talked too much...more practical example step by step

par Shawn W

Sep 19, 2019

A bit difficult when introducing the ML history

par vishnu p T

May 23, 2020

quiet difficult to undertand

par Saurav K

Jul 21, 2019

It's not much helpful

par Vinit K

Jan 22, 2019

Very Basic again

par KimNamho

Apr 12, 2019

thank you

par Edward H

Mar 03, 2020

The course content is fine. My big beef is with the last lab. Does not, will not run on loading the data. I experienced so much trouble that I looked into some guidance with the answer video. A character by character exact copy of the solution will not run to load the data. Total waste of time.

Yes, I realize that I was "cheating" by using the solution as my input to the lab. But after having tried (and failing miserably) to get the answer on my own, and not even being able to get past the very first hurdle, I had to try to get something working. I soon found that it wasn't just my lack of experience, since the provided solution did not work either.

par Brennon B

May 28, 2018

Google has clearly put a great deal of effort into constructing and polishing this course. However, the certificate is really nothing more than a participation trophy. I understand that putting the course materials (videos, demos, etc.) are time-consuming. An exceptional course, though, needs to actually test that the learner has, indeed, learned. When all of the labs/assignments require nothing more than clicking through them, they fall far short in this respect.

par Soroosh R

Feb 15, 2019

The instructors were talking most of the time in a monotonous way without showing proper slides or elaborating the materials. Overall it was a very poor introduction of the ML. The two labs were good, however it was surprising to me that they did not commented out the notebook codes!

par Ragy I

Mar 20, 2019

Maths and ML stuff are explained very poorly... very rushed and people speaking are clearly reading from a script which makes it difficult to understand and follow on =

par Ronnie R

May 22, 2018

instructor more plain and hard to hear so many math concepts just with words not visual enough, seems like instrctor is not breaking it down like the first course.

par Srikar K

May 01, 2018

The LABs in this course did not work for me. I was not able to open DataLab in my Lab sessions. This is quite frustrating to me.

par Sean S

Jan 28, 2019

The labs really just lay everything out for you, and don't challenge you to learn anything for yourself.

par Kevin D B

Sep 16, 2019

It's covering a lot but brushing over things too quickly and using a ton of jargon.

par Sebastian R

Oct 19, 2019

Weak: Long on telling you how great google is, short on technical skills.

par Johny C

Jun 29, 2020

These are plain lectures. Ng's are way better.

par Thomas V

Nov 15, 2018

No real implementation

par Francesco C

Jul 12, 2018

labs not really useful

par Ligeng X

Nov 09, 2018

Barely learn anything

par Yaron K

Jul 14, 2018

It's unclear for who this course is meant. It mixes basics like train-validate-test with lectures that use machine learning terms that only have meaning to someone who has already knows ML terminology. If you're looking for a good introduction to ML - check out Andrew Ng's course.

par David S

Aug 16, 2019

"Short History of ML" was good, if kind of light. The rest of this course is flaming garbage. Zero topic organization. Material is poorly explained. Labs are poorly detailed and in some cases don't work out of the box. Seriously, skip this course and take Andrew Ng's instead.

par john f d

Jul 18, 2018

Labs vms are to slow. Speaker is difficult to understand. Mic varies and speech pattern is not clear. The presentations need some graphics rather than a guy talking. Sketch out the ideas on a white board rather than talking 5 minutes to a single slide.

par Neeraj

May 28, 2018

looks more like a promotional course from google instead of an acutal learning experience.

Also the labs have no data on the code used, it is assumed the learners are well acquianted with the technology used that is specific to google.

par Mike W

Jun 22, 2019

The notebook based demos are unfortunately pretty useless as labs. All of these courses would be much improved with real labs that require the student to build the system.

par Arman A

Apr 11, 2019

Pros: Tensorflow is an excellent framework for deep learning

Cons :

1- The way this material is designed is 10 X SHIT

2- Either teach properly or don't teach at all.