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Avis et commentaires pour l'étudiant pour Launching into Machine Learning par Google Cloud

4.6
3,036 notes
342 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 COMPLETION CHALLENGE Complete any GCP specialization from November 5 - November 30, 2019 for an opportunity to receive a GCP t-shirt (while supplies last). Check Discussion Forums for details....

Meilleurs avis

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 :)

PA

Aug 04, 2018

Good course, covering all the basics about machine learning and most importantly, everything that surrounds an ml project and you need to take into account to make your ml project successful.

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326 - 340 sur 340 Examens pour Launching into Machine Learning

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 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 Ehsan F

Nov 13, 2018

This is the most superficial course I have ever taken. I just waisted my time.

par Praveen K M

Feb 17, 2019

I'm not able to access the video lectures even though I purchased and completed this course 6 months back

par Karim E

Aug 08, 2018

not well structured and lack handouts

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 Chi S S

Sep 02, 2018

Did not learn much! Poorly instructed courses.

par Diretnan D

Nov 05, 2018

Too much scary information provided at once combined with the mindbending sql queries and data parsing

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 sasidhar m

Jul 16, 2018

No hands on learning.

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 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.

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 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.