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Applied AI with DeepLearning(으)로 돌아가기

IBM의 Applied AI with DeepLearning 학습자 리뷰 및 피드백

4.5
642개의 평가
98개의 리뷰

강좌 소개

>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. We’ll learn about the fundamentals of Linear Algebra and Neural Networks. Then we introduce the most popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML. Keras and TensorFlow are making up the greatest portion of this course. We learn about Anomaly Detection, Time Series Forecasting, Image Recognition and Natural Language Processing by building up models using Keras on real-life examples from IoT (Internet of Things), Financial Marked Data, Literature or Image Databases. Finally, we learn how to scale those artificial brains using Kubernetes, Apache Spark and GPUs. IMPORTANT: THIS COURSE ALONE IS NOT SUFFICIENT TO OBTAIN THE "IBM Watson IoT Certified Data Scientist certificate". You need to take three other courses where two of them are currently built. The Specialization will be ready late spring, early summer 2018 Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give your ideas for turbocharging successful creation and deployment of DeepLearning models. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this course will help serve as your guide. Prerequisites: Some coding skills are necessary. Preferably python, but any other programming language will do fine. Also some basic understanding of math (linear algebra) is a plus, but we will cover that part in the first week as well. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging....

최상위 리뷰

RC

Apr 26, 2018

It was really great learning with coursera and I loved the course. The way faculty teaches here is just awesome as they are very much clear and helped a lot while learning this coursea

BS

Aug 08, 2019

Gave a good hands-on with IBM Watson studio notebooks. Also a good overview of LSTM's, Keras, Predictive maintenance. Good stuff, keep it going

필터링 기준:

Applied AI with DeepLearning의 98개 리뷰 중 51~75

교육 기관: Carlos F C d S e S

Dec 29, 2019

It is an amazing course!

교육 기관: Julien P

Sep 25, 2019

Very nice and complete.

교육 기관: Fernando C

Mar 03, 2019

The course is great!

교육 기관: Ayesha S

Feb 22, 2019

It boosted my skills

교육 기관: PURNANAND W

Jul 30, 2018

Awesome knowledge !!

교육 기관: Madan K

Dec 11, 2019

Excellent Course

교육 기관: PV R K

Oct 18, 2019

excellent course

교육 기관: Deleted A

Jun 05, 2018

amazing course

교육 기관: Gustavo H M d C

Nov 05, 2019

Very good!!!

교육 기관: FREDDY Y

Jun 06, 2019

great course

교육 기관: SRAVANKUMAR E

Feb 02, 2020

good course

교육 기관: SHIVANI Y

Sep 24, 2019

ossum

교육 기관: Waleed M S A A A G

Feb 23, 2019

good

교육 기관: A.Basit M

May 08, 2018

nice

교육 기관: Naveen M N S

Feb 18, 2018

Very hands-on course. Enjoyed the width of problems that were solved. IBM cloud seems irresistible. Certain sections of the course are too fast. For such sections it will be better if the notebook links are provided in the video/description itself.

교육 기관: Filip G

Oct 09, 2019

Nice course with lots of practical examples. Course is delivered by multiple tutors with different styles and level of detail. Overall good introductory course into neural networks, scaling and deployment.

교육 기관: Giovani F M

Jan 24, 2020

I've learned a lot from this course. I've very much the Time Series Forecasting Section Explanation. The notebook is detailed and the concepts very well discussed.

교육 기관: Dmitry B

Jan 11, 2019

This course is packed with info on different deep learning techniques and libraries. Not all of them can be found in exercises though.

교육 기관: Saurabh W

Mar 12, 2018

One of the great course from IBM Watson .Really one should take this one if intrested in Deep Learning.

교육 기관: Chandan C

Feb 09, 2020

Exercises let me explore the topic further which was very helpful for my learning

교육 기관: Sourastra N

Jul 26, 2019

The course needs to allow the students to build their own model.

교육 기관: Dmitry G

Jul 19, 2018

Concise intro to much needed big data machine learning solutions

교육 기관: Victor d O

Jan 09, 2019

I think we need in this module more pratical assignments.

교육 기관: PRASHANT K R

Jun 07, 2018

very nice course it gives more insight to deep learning.

교육 기관: Jair M

May 22, 2019

Some videos are missing, but anyway is a great course